From c88a8e31715f6f9a4d092268bd24532cdb5a124c Mon Sep 17 00:00:00 2001
From: vijay-arya <vijay.arya@in.ibm.com>
Date: Fri, 18 Oct 2019 11:22:20 +0530
Subject: [PATCH] lime and shap

---
 examples/lime/LIME.ipynb | 269 +++++++++++++------------
 examples/shap/SHAP.ipynb | 416 ++++++++++++++-------------------------
 2 files changed, 289 insertions(+), 396 deletions(-)

diff --git a/examples/lime/LIME.ipynb b/examples/lime/LIME.ipynb
index 8495304..f1a97d2 100644
--- a/examples/lime/LIME.ipynb
+++ b/examples/lime/LIME.ipynb
@@ -4,23 +4,22 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Tutorial to invoke LIME explainers via AIX360\n",
+    "# Tutorial to invoke LIME explainers via aix360\n",
     "\n",
-    "There are two ways to use LIME for explanations after installing aix360:\n",
-    "- Since LIME is installed along with other libraries in aix360, it can simply be invoked directly.\n",
-    "- LIME can also be invoked in a manner similar to other algorithms in aix360 via the implemented wrapper classes.\n",
+    "There are two ways to use [LIME](https://github.com/marcotcr/lime) explainers after installing aix360:\n",
+    "- [Approach 1  (aix360 style)](#approach1): LIME explainers can be invoked in a manner similar to other explainer algorithms in aix360 via the implemented wrapper classes.\n",
+    "- [Approach 2 (original style)](#approach2): Since LIME comes pre-installed in aix360, the explainers can simply be invoked directly.\n",
     "\n",
-    "This notebook shows both these approaches to invoke LIME in aix360. The notebook is based on the following example from the original LIME tutorial: \n",
-    "https://github.com/marcotcr/lime/blob/master/doc/notebooks/Lime%20-%20multiclass.ipynb\n"
+    "This notebook showcases both these approaches to invoke LIME. The notebook is based on the following example from the original LIME tutorial: https://marcotcr.github.io/lime/tutorials/Lime%20-%20multiclass.html"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Approach 1 (original style)\n",
-    "### LIME Text Example \n",
-    "- Example from https://marcotcr.github.io/lime/tutorials/Lime%20-%20multiclass.html"
+    "## Approach 1  (aix360 style)\n",
+    "<a id='approach1'></a>\n",
+    "- Note the import statement related to LimeTextExplainer"
    ]
   },
   {
@@ -36,7 +35,8 @@
     "import sklearn.ensemble\n",
     "import sklearn.metrics\n",
     "\n",
-    "from lime.lime_text import LimeTextExplainer"
+    "# Importing LimeTextExplainer (aix360 sytle)\n",
+    "from aix360.algorithms.lime import LimeTextExplainer"
    ]
   },
   {
@@ -44,6 +44,24 @@
    "execution_count": 2,
    "metadata": {},
    "outputs": [],
+   "source": [
+    "# Supress jupyter warnings if required for cleaner output\n",
+    "import warnings\n",
+    "warnings.simplefilter('ignore')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Fetching data, training a classifier"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "from sklearn.datasets import fetch_20newsgroups\n",
     "newsgroups_train = fetch_20newsgroups(subset='train')\n",
@@ -56,7 +74,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -73,7 +91,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -84,7 +102,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -93,7 +111,7 @@
        "MultinomialNB(alpha=0.01, class_prior=None, fit_prior=True)"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -106,7 +124,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -115,7 +133,7 @@
        "0.8350184193998174"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -125,9 +143,16 @@
     "sklearn.metrics.f1_score(newsgroups_test.target, pred, average='weighted')"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Explaining predictions using lime"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -137,7 +162,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -153,15 +178,6 @@
     "print(c.predict_proba([newsgroups_test.data[0]]).round(3))"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "explainer = LimeTextExplainer(class_names=class_names)"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 10,
@@ -171,12 +187,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "<class 'lime.lime_text.LimeTextExplainer'>\n"
+      "<class 'aix360.algorithms.lime.lime_wrapper.LimeTextExplainer'>\n"
      ]
     }
    ],
    "source": [
-    "print(type(explainer))"
+    "limeexplainer = LimeTextExplainer(class_names=class_names)\n",
+    "print(type(limeexplainer))"
    ]
   },
   {
@@ -184,14 +201,6 @@
    "execution_count": 11,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/lime/lime_text.py:116: FutureWarning: split() requires a non-empty pattern match.\n",
-      "  self.as_list = [s for s in splitter.split(self.raw) if s]\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -204,7 +213,8 @@
    ],
    "source": [
     "idx = 1340\n",
-    "exp = explainer.explain_instance(newsgroups_test.data[idx], c.predict_proba, num_features=6, labels=[0, 17])\n",
+    "# aix360 style for explaining input instances\n",
+    "exp = limeexplainer.explain_instance(newsgroups_test.data[idx], c.predict_proba, num_features=6, labels=[0, 17])\n",
     "print('Document id: %d' % idx)\n",
     "print('Predicted class =', class_names[nb.predict(test_vectors[idx]).reshape(1,-1)[0,0]])\n",
     "print('True class: %s' % class_names[newsgroups_test.target[idx]])"
@@ -220,20 +230,20 @@
      "output_type": "stream",
      "text": [
       "Explanation for class atheism\n",
-      "('Caused', 0.2638134141747723)\n",
-      "('Rice', 0.138346697297952)\n",
-      "('Genocide', 0.12506034401934968)\n",
-      "('owlnet', -0.08968526910905454)\n",
-      "('scri', -0.08426182410065453)\n",
-      "('Semitic', -0.07968947032986141)\n",
+      "('Caused', 0.2598306611703779)\n",
+      "('Rice', 0.1476407287363688)\n",
+      "('Genocide', 0.13182300286384235)\n",
+      "('scri', -0.09419412002335747)\n",
+      "('certainty', -0.09272741554383297)\n",
+      "('owlnet', -0.08993298975187172)\n",
       "\n",
       "Explanation for class mideast\n",
-      "('fsu', -0.06012358222232414)\n",
-      "('Theism', -0.05266356722531139)\n",
-      "('Luther', -0.049997961626805004)\n",
-      "('jews', 0.035879721280743154)\n",
-      "('Caused', -0.03457976903151407)\n",
-      "('PBS', 0.034166969785271686)\n"
+      "('fsu', -0.05535199329931831)\n",
+      "('Theism', -0.05150493402341905)\n",
+      "('Luther', -0.04742295494991691)\n",
+      "('jews', 0.03810985477960863)\n",
+      "('Caused', -0.037706845450166455)\n",
+      "('PBS', 0.031228586744514376)\n"
      ]
     }
    ],
@@ -250,14 +260,6 @@
    "execution_count": 13,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/lime/lime_text.py:116: FutureWarning: split() requires a non-empty pattern match.\n",
-      "  self.as_list = [s for s in splitter.split(self.raw) if s]\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -267,7 +269,8 @@
     }
    ],
    "source": [
-    "exp = explainer.explain_instance(newsgroups_test.data[idx], c.predict_proba, num_features=6, top_labels=2)\n",
+    "# aix360 style for explaining input instances\n",
+    "exp = limeexplainer.explain_instance(newsgroups_test.data[idx], c.predict_proba, num_features=6, top_labels=2)\n",
     "print(exp.available_labels())"
    ]
   },
@@ -37369,10 +37372,10 @@
        "/***/ })\n",
        "/******/ ]);\n",
        "//# sourceMappingURL=bundle.js.map </script></head><body>\n",
-       "        <div class=\"lime top_div\" id=\"top_divMW9KPW4C95KBNJK\"></div>\n",
+       "        <div class=\"lime top_div\" id=\"top_div098CBPQH0XV9JQI\"></div>\n",
        "        \n",
        "        <script>\n",
-       "        var top_div = d3.select('#top_divMW9KPW4C95KBNJK').classed('lime top_div', true);\n",
+       "        var top_div = d3.select('#top_div098CBPQH0XV9JQI').classed('lime top_div', true);\n",
        "        \n",
        "            var pp_div = top_div.append('div')\n",
        "                                .classed('lime predict_proba', true);\n",
@@ -37384,10 +37387,10 @@
        "            var exp = new lime.Explanation([\"atheism\", \"graphics\", \"ms-windows.misc\", \"pc.hardware\", \"mac.hardware\", \"x\", \"misc.forsale\", \"autos\", \"motorcycles\", \"baseball\", \"hockey\", \"crypt\", \"electronics\", \"med\", \"space\", \"christian\", \"guns\", \"mideast\", \"politics.misc\", \"religion.misc\"]);\n",
        "        \n",
        "                exp_div = top_div.append('div').classed('lime explanation', true);\n",
-       "                exp.show([[\"Caused\", 0.26172088740087246], [\"Rice\", 0.134340905558955], [\"Genocide\", 0.1310044187227226], [\"scri\", -0.09395256838931401], [\"owlnet\", -0.0859715927132927], [\"certainty\", -0.08386045754386767]], 0, exp_div);\n",
+       "                exp.show([[\"Caused\", 0.26133632856662387], [\"Rice\", 0.13695355035302995], [\"Genocide\", 0.12807783076647114], [\"certainty\", -0.09326687147128634], [\"owlnet\", -0.09144122893155225], [\"scri\", -0.08639643324857654]], 0, exp_div);\n",
        "                \n",
        "                exp_div = top_div.append('div').classed('lime explanation', true);\n",
-       "                exp.show([[\"Caused\", -0.19304471058720868], [\"Genocide\", -0.10740724254002221], [\"scri\", 0.09670648313756486], [\"fsu\", 0.09332760080549678], [\"owlnet\", 0.08245717193535658], [\"Luther\", 0.0794373317233636]], 15, exp_div);\n",
+       "                exp.show([[\"Caused\", -0.18557991232936014], [\"Genocide\", -0.09796558866874504], [\"Luthers\", 0.08880589418601413], [\"owlnet\", 0.08800418198520617], [\"scri\", 0.08654292365314807], [\"certainty\", 0.08594434218527054]], 15, exp_div);\n",
        "                \n",
        "        var raw_div = top_div.append('div');\n",
        "        </script>\n",
@@ -74503,10 +74506,10 @@
        "/***/ })\n",
        "/******/ ]);\n",
        "//# sourceMappingURL=bundle.js.map </script></head><body>\n",
-       "        <div class=\"lime top_div\" id=\"top_divCBO40R8ZU1MEVAT\"></div>\n",
+       "        <div class=\"lime top_div\" id=\"top_divP714N8C6HF86I2Z\"></div>\n",
        "        \n",
        "        <script>\n",
-       "        var top_div = d3.select('#top_divCBO40R8ZU1MEVAT').classed('lime top_div', true);\n",
+       "        var top_div = d3.select('#top_divP714N8C6HF86I2Z').classed('lime top_div', true);\n",
        "        \n",
        "            var pp_div = top_div.append('div')\n",
        "                                .classed('lime predict_proba', true);\n",
@@ -74518,10 +74521,10 @@
        "            var exp = new lime.Explanation([\"atheism\", \"graphics\", \"ms-windows.misc\", \"pc.hardware\", \"mac.hardware\", \"x\", \"misc.forsale\", \"autos\", \"motorcycles\", \"baseball\", \"hockey\", \"crypt\", \"electronics\", \"med\", \"space\", \"christian\", \"guns\", \"mideast\", \"politics.misc\", \"religion.misc\"]);\n",
        "        \n",
        "                exp_div = top_div.append('div').classed('lime explanation', true);\n",
-       "                exp.show([[\"Caused\", 0.26172088740087246], [\"Rice\", 0.134340905558955], [\"Genocide\", 0.1310044187227226], [\"scri\", -0.09395256838931401], [\"owlnet\", -0.0859715927132927], [\"certainty\", -0.08386045754386767]], 0, exp_div);\n",
+       "                exp.show([[\"Caused\", 0.26133632856662387], [\"Rice\", 0.13695355035302995], [\"Genocide\", 0.12807783076647114], [\"certainty\", -0.09326687147128634], [\"owlnet\", -0.09144122893155225], [\"scri\", -0.08639643324857654]], 0, exp_div);\n",
        "                \n",
        "        var raw_div = top_div.append('div');\n",
-       "            exp.show_raw_text([[\"Caused\", 82, 0.26172088740087246], [\"Caused\", 680, 0.26172088740087246], [\"Rice\", 125, 0.134340905558955], [\"Rice\", 1138, 0.134340905558955], [\"Rice\", 1160, 0.134340905558955], [\"Genocide\", 70, 0.1310044187227226], [\"Genocide\", 668, 0.1310044187227226], [\"scri\", 208, -0.09395256838931401], [\"owlnet\", 12, -0.0859715927132927], [\"certainty\", 1047, -0.08386045754386767]], 0, \"From: conor@owlnet.rice.edu (Conor Frederick Prischmann)\\nSubject: Re: Genocide is Caused by Theism : Evidence?\\nOrganization: Rice University\\nLines: 23\\n\\nIn article |C60A0s.DvI@mailer.cc.fsu.edu| dekorte@dirac.scri.fsu.edu (Stephen L. DeKorte) writes:\\n|\\n|I saw a 3 hour show on PBS the other day about the history of the\\n|Jews. Appearently, the Cursades(a religious war agianst the muslilams\\n|in 'the holy land') sparked the widespread persecution of muslilams \\n|and jews in europe. Among the supporters of the persiecution, were none \\n|other than Martin Luther, and the Vatican.\\n|\\n|Later, Hitler would use Luthers writings to justify his own treatment\\n|of the jews.\\n|| Genocide is Caused by Theism : Evidence?\\n\\nHeck, I remember reading a quote of Luther as something like: \\\"Jews should\\nbe shot like deer.\\\"  And of course much Catholic doctrine for centuries was \\nextremely anti-Semitic.\\n\\n\\n\\n-- \\n\\\"Are you so sure that your truth and your justice are worth more than the\\ntruths and justices of other centuries?\\\" - Simone de Beauvoir\\n\\\"Where is there a certainty that rises above all doubt and withstands all\\ncritique?\\\" - Karl Jaspers          Rice University, Will Rice College '96\\n\", raw_div, true);\n",
+       "            exp.show_raw_text([[\"Caused\", 82, 0.26133632856662387], [\"Caused\", 680, 0.26133632856662387], [\"Rice\", 125, 0.13695355035302995], [\"Rice\", 1138, 0.13695355035302995], [\"Rice\", 1160, 0.13695355035302995], [\"Genocide\", 70, 0.12807783076647114], [\"Genocide\", 668, 0.12807783076647114], [\"certainty\", 1047, -0.09326687147128634], [\"owlnet\", 12, -0.09144122893155225], [\"scri\", 208, -0.08639643324857654]], 0, \"From: conor@owlnet.rice.edu (Conor Frederick Prischmann)\\nSubject: Re: Genocide is Caused by Theism : Evidence?\\nOrganization: Rice University\\nLines: 23\\n\\nIn article |C60A0s.DvI@mailer.cc.fsu.edu| dekorte@dirac.scri.fsu.edu (Stephen L. DeKorte) writes:\\n|\\n|I saw a 3 hour show on PBS the other day about the history of the\\n|Jews. Appearently, the Cursades(a religious war agianst the muslilams\\n|in 'the holy land') sparked the widespread persecution of muslilams \\n|and jews in europe. Among the supporters of the persiecution, were none \\n|other than Martin Luther, and the Vatican.\\n|\\n|Later, Hitler would use Luthers writings to justify his own treatment\\n|of the jews.\\n|| Genocide is Caused by Theism : Evidence?\\n\\nHeck, I remember reading a quote of Luther as something like: \\\"Jews should\\nbe shot like deer.\\\"  And of course much Catholic doctrine for centuries was \\nextremely anti-Semitic.\\n\\n\\n\\n-- \\n\\\"Are you so sure that your truth and your justice are worth more than the\\ntruths and justices of other centuries?\\\" - Simone de Beauvoir\\n\\\"Where is there a certainty that rises above all doubt and withstands all\\ncritique?\\\" - Karl Jaspers          Rice University, Will Rice College '96\\n\", raw_div, true);\n",
        "            \n",
        "        </script>\n",
        "        </body></html>"
@@ -74542,9 +74545,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Approach 2  (aix360 style)\n",
-    "### LIME Text Example \n",
-    "- Example from https://marcotcr.github.io/lime/tutorials/Lime%20-%20multiclass.html"
+    "## Approach 2 (original style)\n",
+    "<a id='approach2'></a>\n",
+    "- Note the import statement related to LimeTextExplainer"
    ]
   },
   {
@@ -74560,7 +74563,8 @@
     "import sklearn.ensemble\n",
     "import sklearn.metrics\n",
     "\n",
-    "from aix360.algorithms.lime import LimeTextExplainer"
+    "# Importing LimeTextExplainer (original style)\n",
+    "from lime.lime_text import LimeTextExplainer"
    ]
   },
   {
@@ -74568,6 +74572,24 @@
    "execution_count": 17,
    "metadata": {},
    "outputs": [],
+   "source": [
+    "# Supress jupyter warnings if required for cleaner output\n",
+    "import warnings\n",
+    "warnings.simplefilter('ignore')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Fetching data, training a classifier"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "from sklearn.datasets import fetch_20newsgroups\n",
     "newsgroups_train = fetch_20newsgroups(subset='train')\n",
@@ -74580,7 +74602,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -74597,7 +74619,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -74608,7 +74630,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -74617,7 +74639,7 @@
        "MultinomialNB(alpha=0.01, class_prior=None, fit_prior=True)"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -74630,8 +74652,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
+   "execution_count": 22,
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [
     {
      "data": {
@@ -74639,7 +74663,7 @@
        "0.8350184193998174"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -74649,9 +74673,16 @@
     "sklearn.metrics.f1_score(newsgroups_test.target, pred, average='weighted')"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Explaining predictions using lime"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -74661,8 +74692,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
+   "execution_count": 24,
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -74677,15 +74710,6 @@
     "print(c.predict_proba([newsgroups_test.data[0]]).round(3))"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "explainer = LimeTextExplainer(class_names=class_names)"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 25,
@@ -74695,11 +74719,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "<class 'aix360.algorithms.lime.lime_wrapper.LimeTextExplainer'>\n"
+      "<class 'lime.lime_text.LimeTextExplainer'>\n"
      ]
     }
    ],
    "source": [
+    "explainer = LimeTextExplainer(class_names=class_names)\n",
     "print(type(explainer))"
    ]
   },
@@ -74708,14 +74733,6 @@
    "execution_count": 26,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/lime/lime_text.py:116: FutureWarning: split() requires a non-empty pattern match.\n",
-      "  self.as_list = [s for s in splitter.split(self.raw) if s]\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -74728,6 +74745,7 @@
    ],
    "source": [
     "idx = 1340\n",
+    "# LIME original style for explaining input instances\n",
     "exp = explainer.explain_instance(newsgroups_test.data[idx], c.predict_proba, num_features=6, labels=[0, 17])\n",
     "print('Document id: %d' % idx)\n",
     "print('Predicted class =', class_names[nb.predict(test_vectors[idx]).reshape(1,-1)[0,0]])\n",
@@ -74744,20 +74762,20 @@
      "output_type": "stream",
      "text": [
       "Explanation for class atheism\n",
-      "('Caused', 0.2597060457934411)\n",
-      "('Rice', 0.13750116781221147)\n",
-      "('Genocide', 0.12709403856842216)\n",
-      "('owlnet', -0.09213085168650197)\n",
-      "('certainty', -0.08533532387206953)\n",
-      "('scri', -0.0815491273299416)\n",
+      "('Caused', 0.2601154192014532)\n",
+      "('Rice', 0.14380270774013457)\n",
+      "('Genocide', 0.12202776283712338)\n",
+      "('owlnet', -0.0894833391913411)\n",
+      "('scri', -0.08839334155116563)\n",
+      "('certainty', -0.08588797496264497)\n",
       "\n",
       "Explanation for class mideast\n",
-      "('fsu', -0.05853835334882245)\n",
-      "('Theism', -0.05311524141087401)\n",
-      "('Luther', -0.05238291745855021)\n",
-      "('jews', 0.03575948416506709)\n",
-      "('Rice', -0.0345554947784977)\n",
-      "('PBS', 0.02977066446182471)\n"
+      "('fsu', -0.053283740516256506)\n",
+      "('Theism', -0.05103765776729127)\n",
+      "('Luther', -0.04556208403350433)\n",
+      "('jews', 0.03472601688974457)\n",
+      "('Caused', -0.03463184676401465)\n",
+      "('PBS', 0.02914905322207845)\n"
      ]
     }
    ],
@@ -74774,14 +74792,6 @@
    "execution_count": 28,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/lime/lime_text.py:116: FutureWarning: split() requires a non-empty pattern match.\n",
-      "  self.as_list = [s for s in splitter.split(self.raw) if s]\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -74791,6 +74801,7 @@
     }
    ],
    "source": [
+    "# LIME original style for explaining input instances\n",
     "exp = explainer.explain_instance(newsgroups_test.data[idx], c.predict_proba, num_features=6, top_labels=2)\n",
     "print(exp.available_labels())"
    ]
@@ -111893,10 +111904,10 @@
        "/***/ })\n",
        "/******/ ]);\n",
        "//# sourceMappingURL=bundle.js.map </script></head><body>\n",
-       "        <div class=\"lime top_div\" id=\"top_divV91L1G3HR6QKGFZ\"></div>\n",
+       "        <div class=\"lime top_div\" id=\"top_div44FYCKITOE6CY7V\"></div>\n",
        "        \n",
        "        <script>\n",
-       "        var top_div = d3.select('#top_divV91L1G3HR6QKGFZ').classed('lime top_div', true);\n",
+       "        var top_div = d3.select('#top_div44FYCKITOE6CY7V').classed('lime top_div', true);\n",
        "        \n",
        "            var pp_div = top_div.append('div')\n",
        "                                .classed('lime predict_proba', true);\n",
@@ -111908,10 +111919,10 @@
        "            var exp = new lime.Explanation([\"atheism\", \"graphics\", \"ms-windows.misc\", \"pc.hardware\", \"mac.hardware\", \"x\", \"misc.forsale\", \"autos\", \"motorcycles\", \"baseball\", \"hockey\", \"crypt\", \"electronics\", \"med\", \"space\", \"christian\", \"guns\", \"mideast\", \"politics.misc\", \"religion.misc\"]);\n",
        "        \n",
        "                exp_div = top_div.append('div').classed('lime explanation', true);\n",
-       "                exp.show([[\"Caused\", 0.2542949590321917], [\"Rice\", 0.14820062081839447], [\"Genocide\", 0.1264715788407395], [\"scri\", -0.08685870260460596], [\"Semitic\", -0.08499007101377468], [\"owlnet\", -0.08449658701926308]], 0, exp_div);\n",
+       "                exp.show([[\"Caused\", 0.2592971163904119], [\"Rice\", 0.13779941851932948], [\"Genocide\", 0.12354259738158209], [\"owlnet\", -0.08650666509608868], [\"scri\", -0.08496093619027346], [\"certainty\", -0.08027170285272602]], 0, exp_div);\n",
        "                \n",
        "                exp_div = top_div.append('div').classed('lime explanation', true);\n",
-       "                exp.show([[\"Caused\", -0.19346183182029286], [\"Genocide\", -0.08937348376452159], [\"Semitic\", 0.08464993111649723], [\"Luther\", 0.08449013466054511], [\"doctrine\", 0.08388065845607018], [\"scri\", 0.08250413964840779]], 15, exp_div);\n",
+       "                exp.show([[\"Caused\", -0.1939259766421773], [\"fsu\", 0.09431134302617511], [\"Genocide\", -0.08993015748528403], [\"scri\", 0.08682485360947678], [\"owlnet\", 0.07996346348581546], [\"Semitic\", 0.07915917070801216]], 15, exp_div);\n",
        "                \n",
        "        var raw_div = top_div.append('div');\n",
        "        </script>\n",
@@ -111932,7 +111943,9 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {},
+   "metadata": {
+    "scrolled": false
+   },
    "outputs": [
     {
      "data": {
@@ -149027,10 +149040,10 @@
        "/***/ })\n",
        "/******/ ]);\n",
        "//# sourceMappingURL=bundle.js.map </script></head><body>\n",
-       "        <div class=\"lime top_div\" id=\"top_divQI62CDZ6J5O91H5\"></div>\n",
+       "        <div class=\"lime top_div\" id=\"top_divQLH2JW4ITF4207U\"></div>\n",
        "        \n",
        "        <script>\n",
-       "        var top_div = d3.select('#top_divQI62CDZ6J5O91H5').classed('lime top_div', true);\n",
+       "        var top_div = d3.select('#top_divQLH2JW4ITF4207U').classed('lime top_div', true);\n",
        "        \n",
        "            var pp_div = top_div.append('div')\n",
        "                                .classed('lime predict_proba', true);\n",
@@ -149042,10 +149055,10 @@
        "            var exp = new lime.Explanation([\"atheism\", \"graphics\", \"ms-windows.misc\", \"pc.hardware\", \"mac.hardware\", \"x\", \"misc.forsale\", \"autos\", \"motorcycles\", \"baseball\", \"hockey\", \"crypt\", \"electronics\", \"med\", \"space\", \"christian\", \"guns\", \"mideast\", \"politics.misc\", \"religion.misc\"]);\n",
        "        \n",
        "                exp_div = top_div.append('div').classed('lime explanation', true);\n",
-       "                exp.show([[\"Caused\", 0.2542949590321917], [\"Rice\", 0.14820062081839447], [\"Genocide\", 0.1264715788407395], [\"scri\", -0.08685870260460596], [\"Semitic\", -0.08499007101377468], [\"owlnet\", -0.08449658701926308]], 0, exp_div);\n",
+       "                exp.show([[\"Caused\", 0.2592971163904119], [\"Rice\", 0.13779941851932948], [\"Genocide\", 0.12354259738158209], [\"owlnet\", -0.08650666509608868], [\"scri\", -0.08496093619027346], [\"certainty\", -0.08027170285272602]], 0, exp_div);\n",
        "                \n",
        "        var raw_div = top_div.append('div');\n",
-       "            exp.show_raw_text([[\"Caused\", 82, 0.2542949590321917], [\"Caused\", 680, 0.2542949590321917], [\"Rice\", 125, 0.14820062081839447], [\"Rice\", 1138, 0.14820062081839447], [\"Rice\", 1160, 0.14820062081839447], [\"Genocide\", 70, 0.1264715788407395], [\"Genocide\", 668, 0.1264715788407395], [\"scri\", 208, -0.08685870260460596], [\"Semitic\", 877, -0.08499007101377468], [\"owlnet\", 12, -0.08449658701926308]], 0, \"From: conor@owlnet.rice.edu (Conor Frederick Prischmann)\\nSubject: Re: Genocide is Caused by Theism : Evidence?\\nOrganization: Rice University\\nLines: 23\\n\\nIn article |C60A0s.DvI@mailer.cc.fsu.edu| dekorte@dirac.scri.fsu.edu (Stephen L. DeKorte) writes:\\n|\\n|I saw a 3 hour show on PBS the other day about the history of the\\n|Jews. Appearently, the Cursades(a religious war agianst the muslilams\\n|in 'the holy land') sparked the widespread persecution of muslilams \\n|and jews in europe. Among the supporters of the persiecution, were none \\n|other than Martin Luther, and the Vatican.\\n|\\n|Later, Hitler would use Luthers writings to justify his own treatment\\n|of the jews.\\n|| Genocide is Caused by Theism : Evidence?\\n\\nHeck, I remember reading a quote of Luther as something like: \\\"Jews should\\nbe shot like deer.\\\"  And of course much Catholic doctrine for centuries was \\nextremely anti-Semitic.\\n\\n\\n\\n-- \\n\\\"Are you so sure that your truth and your justice are worth more than the\\ntruths and justices of other centuries?\\\" - Simone de Beauvoir\\n\\\"Where is there a certainty that rises above all doubt and withstands all\\ncritique?\\\" - Karl Jaspers          Rice University, Will Rice College '96\\n\", raw_div, true);\n",
+       "            exp.show_raw_text([[\"Caused\", 82, 0.2592971163904119], [\"Caused\", 680, 0.2592971163904119], [\"Rice\", 125, 0.13779941851932948], [\"Rice\", 1138, 0.13779941851932948], [\"Rice\", 1160, 0.13779941851932948], [\"Genocide\", 70, 0.12354259738158209], [\"Genocide\", 668, 0.12354259738158209], [\"owlnet\", 12, -0.08650666509608868], [\"scri\", 208, -0.08496093619027346], [\"certainty\", 1047, -0.08027170285272602]], 0, \"From: conor@owlnet.rice.edu (Conor Frederick Prischmann)\\nSubject: Re: Genocide is Caused by Theism : Evidence?\\nOrganization: Rice University\\nLines: 23\\n\\nIn article |C60A0s.DvI@mailer.cc.fsu.edu| dekorte@dirac.scri.fsu.edu (Stephen L. DeKorte) writes:\\n|\\n|I saw a 3 hour show on PBS the other day about the history of the\\n|Jews. Appearently, the Cursades(a religious war agianst the muslilams\\n|in 'the holy land') sparked the widespread persecution of muslilams \\n|and jews in europe. Among the supporters of the persiecution, were none \\n|other than Martin Luther, and the Vatican.\\n|\\n|Later, Hitler would use Luthers writings to justify his own treatment\\n|of the jews.\\n|| Genocide is Caused by Theism : Evidence?\\n\\nHeck, I remember reading a quote of Luther as something like: \\\"Jews should\\nbe shot like deer.\\\"  And of course much Catholic doctrine for centuries was \\nextremely anti-Semitic.\\n\\n\\n\\n-- \\n\\\"Are you so sure that your truth and your justice are worth more than the\\ntruths and justices of other centuries?\\\" - Simone de Beauvoir\\n\\\"Where is there a certainty that rises above all doubt and withstands all\\ncritique?\\\" - Karl Jaspers          Rice University, Will Rice College '96\\n\", raw_div, true);\n",
        "            \n",
        "        </script>\n",
        "        </body></html>"
diff --git a/examples/shap/SHAP.ipynb b/examples/shap/SHAP.ipynb
index 2fe2079..06155a3 100644
--- a/examples/shap/SHAP.ipynb
+++ b/examples/shap/SHAP.ipynb
@@ -4,13 +4,13 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Tutorial to invoke SHAP explainers via AIX360\n",
+    "# Tutorial to invoke SHAP explainers via aix360\n",
     "\n",
-    "There are two ways to use SHAP for explanations after installing aix360:\n",
-    "- Since SHAP is installed along with other libraries in aix360, it can simply be invoked directly.\n",
-    "- SHAP explainers can also be invoked in a manner similar to other explainer algorithms in aix360 via the implemented wrapper classes.\n",
+    "There are two ways to use [SHAP](https://github.com/slundberg/shap) explainers after installing aix360:\n",
+    "- [Approach 1  (aix360 style)](#approach1): SHAP explainers can be invoked in a manner similar to other explainer algorithms in aix360 via the implemented wrapper classes.\n",
+    "- [Approach 2 (original style)](#approach2): Since SHAP comes pre-installed in aix360, the explainers can simply be invoked directly.\n",
     "\n",
-    "This notebook showcases both these approaches to invoke SHAP via aix360. The notebook is based on the following example from the original SHAP tutorial: \n",
+    "This notebook showcases both these approaches to invoke SHAP. The notebook is based on the following example from the original SHAP tutorial: \n",
     "https://slundberg.github.io/shap/notebooks/Iris%20classification%20with%20scikit-learn.html\n"
    ]
   },
@@ -18,7 +18,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Approach 1 (original style)"
+    "## Approach 1  (aix360 style)\n",
+    "<a id='approach1'></a>\n",
+    "- Note the import statement related to KernelExplainer"
    ]
   },
   {
@@ -33,17 +35,38 @@
     "import sklearn.datasets\n",
     "import sklearn.ensemble\n",
     "import numpy as np\n",
-    "import shap\n",
     "import time\n",
     "np.random.seed(1)\n",
     "\n",
-    "from shap import KernelExplainer"
+    "# Importing shap KernelExplainer (aix360 style)\n",
+    "from aix360.algorithms.shap import KernelExplainer\n",
+    "\n",
+    "# the following import is required for access to shap plotting functions and datasets\n",
+    "import shap"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Supress jupyter warnings if required for cleaner output\n",
+    "import warnings\n",
+    "warnings.simplefilter('ignore')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### K-nearest neighbors"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -75,6 +98,13 @@
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy = 96.66666666666667%\n"
+     ]
     }
    ],
    "source": [
@@ -89,62 +119,66 @@
     "    print(\"Accuracy = {0}%\".format(100*np.sum(f(X_test) == Y_test)/len(Y_test)))\n",
     "    time.sleep(0.5) # to let the print get out before any progress bars\n",
     "\n",
-    "shap.initjs()"
+    "shap.initjs()\n",
+    "\n",
+    "knn = sklearn.neighbors.KNeighborsClassifier()\n",
+    "knn.fit(X_train, Y_train)\n",
+    "\n",
+    "print_accuracy(knn.predict)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### K-nearest neighbors"
+    "### Explain a single prediction from the test set"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Using 120 background data samples could cause slower run times. Consider using shap.kmeans(data, K) to summarize the background as K weighted samples.\n"
+     ]
+    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy = 96.66666666666667%\n"
+      "<class 'aix360.algorithms.shap.shap_wrapper.KernelExplainer'>\n"
      ]
     }
    ],
    "source": [
-    "knn = sklearn.neighbors.KNeighborsClassifier()\n",
-    "knn.fit(X_train, Y_train)\n",
-    "\n",
-    "print_accuracy(knn.predict)"
+    "shapexplainer = KernelExplainer(knn.predict_proba, X_train)\n",
+    "print(type(shapexplainer))"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 5,
    "metadata": {},
+   "outputs": [],
    "source": [
-    "### Explain a single prediction from the test set"
+    "# aix360 style for explaining input instances\n",
+    "shap_values = shapexplainer.explain_instance(X_test.iloc[0,:])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Using 120 background data samples could cause slower run times. Consider using shap.kmeans(data, K) to summarize the background as K weighted samples.\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n"
-     ]
-    },
     {
      "data": {
       "text/html": [
        "\n",
-       "<div id='i6IKEPBZPG2FC5CY7F0FR'>\n",
+       "<div id='iE99RGJQVBORJQL3WT31R'>\n",
        "<div style='color: #900; text-align: center;'>\n",
        "  <b>Visualization omitted, Javascript library not loaded!</b><br>\n",
        "  Have you run `initjs()` in this notebook? If this notebook was from another\n",
@@ -155,7 +189,7 @@
        " <script>\n",
        "   if (window.SHAP) SHAP.ReactDom.render(\n",
        "    SHAP.React.createElement(SHAP.AdditiveForceVisualizer, {\"outNames\": [\"output value\"], \"baseValue\": 0.3250000000000002, \"outValue\": 0.0, \"link\": \"identity\", \"featureNames\": [\"sepal length (cm)\", \"sepal width (cm)\", \"petal length (cm)\", \"petal width (cm)\"], \"features\": {\"0\": {\"effect\": -0.0012499999999999734, \"value\": 5.8}, \"1\": {\"effect\": -0.008750000000000036, \"value\": 2.8}, \"2\": {\"effect\": -0.2979166666666667, \"value\": 5.1}, \"3\": {\"effect\": -0.01708333333333345, \"value\": 2.4}}, \"plot_cmap\": \"RdBu\", \"labelMargin\": 20}),\n",
-       "    document.getElementById('i6IKEPBZPG2FC5CY7F0FR')\n",
+       "    document.getElementById('iE99RGJQVBORJQL3WT31R')\n",
        "  );\n",
        "</script>"
       ],
@@ -163,32 +197,13 @@
        "<IPython.core.display.HTML object>"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "explainer = KernelExplainer(knn.predict_proba, X_train)\n",
-    "shap_values = explainer.shap_values(X_test.iloc[0,:])\n",
-    "shap.force_plot(explainer.expected_value[0], shap_values[0], X_test.iloc[0,:])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'shap.explainers.kernel.KernelExplainer'>\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(type(explainer))"
+    "shap.force_plot(shapexplainer.explainer.expected_value[0], shap_values[0], X_test.iloc[0,:])"
    ]
   },
   {
@@ -200,13 +215,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "d6c4f926b165474997fe5493223434e1",
+       "model_id": "53079d7d468a4a568d975ae624d1d419",
        "version_major": 2,
        "version_minor": 0
       },
@@ -217,76 +232,6 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -294,19 +239,11 @@
       "\n"
      ]
     },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n"
-     ]
-    },
     {
      "data": {
       "text/html": [
        "\n",
-       "<div id='iE5222BQZ6RHHU6T76NMW'>\n",
+       "<div id='iAZOP0OUOPPO5YJIX5HKG'>\n",
        "<div style='color: #900; text-align: center;'>\n",
        "  <b>Visualization omitted, Javascript library not loaded!</b><br>\n",
        "  Have you run `initjs()` in this notebook? If this notebook was from another\n",
@@ -317,7 +254,7 @@
        " <script>\n",
        "   if (window.SHAP) SHAP.ReactDom.render(\n",
        "    SHAP.React.createElement(SHAP.AdditiveForceArrayVisualizer, {\"outNames\": [\"output value\"], \"baseValue\": 0.3250000000000002, \"link\": \"identity\", \"featureNames\": [\"sepal length (cm)\", \"sepal width (cm)\", \"petal length (cm)\", \"petal width (cm)\"], \"explanations\": [{\"outValue\": 0.0, \"simIndex\": 12.0, \"features\": {\"0\": {\"effect\": -0.0012499999999999734, \"value\": 5.8}, \"1\": {\"effect\": -0.008750000000000036, \"value\": 2.8}, \"2\": {\"effect\": -0.2979166666666667, \"value\": 5.1}, \"3\": {\"effect\": -0.01708333333333345, \"value\": 2.4}}}, {\"outValue\": 0.0, \"simIndex\": 29.0, \"features\": {\"0\": {\"effect\": 0.0, \"value\": 6.0}, \"1\": {\"effect\": 0.0, \"value\": 2.2}, \"2\": {\"effect\": -0.3250000000000002, \"value\": 4.0}, \"3\": {\"effect\": 0.0, \"value\": 1.0}}}, {\"outValue\": 1.0, \"simIndex\": 7.0, \"features\": {\"0\": {\"effect\": -0.000833333333333075, \"value\": 5.5}, \"1\": {\"effect\": 0.005833333333333635, \"value\": 4.2}, \"2\": {\"effect\": 0.6672222222222213, \"value\": 1.4}, \"3\": {\"effect\": 0.00277777777777799, \"value\": 0.2}}}, {\"outValue\": 0.0, \"simIndex\": 17.0, \"features\": {\"0\": {\"effect\": 0.0009722222222222077, \"value\": 7.3}, \"1\": {\"effect\": -0.0009722222222222077, \"value\": 2.9}, \"2\": {\"effect\": -0.32402777777777797, \"value\": 6.3}, \"3\": {\"effect\": -0.0009722222222222077, \"value\": 1.8}}}, {\"outValue\": 1.0, \"simIndex\": 8.0, \"features\": {\"0\": {\"effect\": -0.0012499999999996958, \"value\": 5.0}, \"1\": {\"effect\": 0.00458333333333355, \"value\": 3.4}, \"2\": {\"effect\": 0.6670833333333324, \"value\": 1.5}, \"3\": {\"effect\": 0.004583333333333606, \"value\": 0.2}}}, {\"outValue\": 0.0, \"simIndex\": 14.0, \"features\": {\"0\": {\"effect\": 0.0033333333333333826, \"value\": 6.3}, \"1\": {\"effect\": 0.0, \"value\": 3.3}, \"2\": {\"effect\": -0.32083333333333347, \"value\": 6.0}, \"3\": {\"effect\": -0.007500000000000062, \"value\": 2.5}}}, 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\"value\": 2.6}, \"2\": {\"effect\": -0.3250000000000002, \"value\": 4.4}, \"3\": {\"effect\": 0.0, \"value\": 1.2}}}, {\"outValue\": 1.0, \"simIndex\": 1.0, \"features\": {\"0\": {\"effect\": -0.0006944444444441089, \"value\": 4.8}, \"1\": {\"effect\": 0.00013888888888924367, \"value\": 3.0}, \"2\": {\"effect\": 0.6731944444444433, \"value\": 1.4}, \"3\": {\"effect\": 0.002361111111111369, \"value\": 0.3}}}, {\"outValue\": 1.0, \"simIndex\": 5.0, \"features\": {\"0\": {\"effect\": 0.00013888888888907713, \"value\": 5.4}, \"1\": {\"effect\": 0.002361111111111369, \"value\": 3.9}, \"2\": {\"effect\": 0.6709722222222212, \"value\": 1.3}, \"3\": {\"effect\": 0.0015277777777782386, \"value\": 0.4}}}, {\"outValue\": 0.0, \"simIndex\": 13.0, \"features\": {\"0\": {\"effect\": -0.0002777777777777102, \"value\": 5.6}, \"1\": {\"effect\": -0.005555555555555591, \"value\": 2.8}, \"2\": {\"effect\": -0.3125000000000001, \"value\": 4.9}, \"3\": {\"effect\": -0.006666666666666765, \"value\": 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2.8}, \"2\": {\"effect\": -0.3220833333333335, \"value\": 4.8}, \"3\": {\"effect\": -0.0018055555555556158, \"value\": 1.8}}}, {\"outValue\": 1.0, \"simIndex\": 4.0, \"features\": {\"0\": {\"effect\": 0.00041666666666689833, \"value\": 4.6}, \"1\": {\"effect\": 0.0015277777777780166, \"value\": 3.6}, \"2\": {\"effect\": 0.6718055555555547, \"value\": 1.0}, \"3\": {\"effect\": 0.0012500000000001954, \"value\": 0.2}}}, {\"outValue\": 1.0, \"simIndex\": 10.0, \"features\": {\"0\": {\"effect\": 0.006250000000000255, \"value\": 5.1}, \"1\": {\"effect\": 0.029861111111111283, \"value\": 3.8}, \"2\": {\"effect\": 0.6059722222222216, \"value\": 1.9}, \"3\": {\"effect\": 0.032916666666666705, \"value\": 0.4}}}, {\"outValue\": 0.0, \"simIndex\": 20.0, \"features\": {\"0\": {\"effect\": 0.0, \"value\": 6.2}, \"1\": {\"effect\": 0.0, \"value\": 2.9}, \"2\": {\"effect\": -0.3250000000000002, \"value\": 4.3}, \"3\": {\"effect\": 0.0, \"value\": 1.3}}}, {\"outValue\": 0.0, \"simIndex\": 15.0, \"features\": {\"0\": {\"effect\": 0.0005555555555555314, \"value\": 5.0}, \"1\": {\"effect\": -0.0038888888888888584, \"value\": 2.3}, \"2\": {\"effect\": -0.31833333333333347, \"value\": 3.3}, \"3\": {\"effect\": -0.0033333333333334103, \"value\": 1.0}}}, {\"outValue\": 1.0, \"simIndex\": 9.0, \"features\": {\"0\": {\"effect\": -0.0020833333333329374, \"value\": 5.0}, \"1\": {\"effect\": 0.0065277777777779655, \"value\": 3.4}, \"2\": {\"effect\": 0.6629166666666656, \"value\": 1.6}, \"3\": {\"effect\": 0.007638888888889195, \"value\": 0.4}}}], \"plot_cmap\": \"RdBu\", \"ordering_keys\": null, \"ordering_keys_time_format\": null}),\n",
-       "    document.getElementById('iE5222BQZ6RHHU6T76NMW')\n",
+       "    document.getElementById('iAZOP0OUOPPO5YJIX5HKG')\n",
        "  );\n",
        "</script>"
       ],
@@ -325,26 +262,29 @@
        "<IPython.core.display.HTML object>"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "shap_values = explainer.shap_values(X_test)\n",
-    "shap.force_plot(explainer.expected_value[0], shap_values[0], X_test)"
+    "# aix360 style for explaining input instances\n",
+    "shap_values = shapexplainer.explain_instance(X_test)\n",
+    "shap.force_plot(shapexplainer.explainer.expected_value[0], shap_values[0], X_test)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Approach 2  (AIX360 style)"
+    "## Approach 2 (original style)\n",
+    "<a id='approach2'></a>\n",
+    "- Note the last import statement related to KernelExplainer"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -354,16 +294,35 @@
     "import sklearn.datasets\n",
     "import sklearn.ensemble\n",
     "import numpy as np\n",
-    "import shap\n",
     "import time\n",
     "np.random.seed(1)\n",
     "\n",
-    "from aix360.algorithms.shap import KernelExplainer"
+    "# Importing shap KernelExplainer (original style)\n",
+    "import shap\n",
+    "from shap import KernelExplainer"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Supress jupyter warnings if required for cleaner output\n",
+    "import warnings\n",
+    "warnings.simplefilter('ignore')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### K-nearest neighbors"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -396,6 +355,13 @@
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy = 96.66666666666667%\n"
+     ]
     }
    ],
    "source": [
@@ -410,48 +376,56 @@
     "    print(\"Accuracy = {0}%\".format(100*np.sum(f(X_test) == Y_test)/len(Y_test)))\n",
     "    time.sleep(0.5) # to let the print get out before any progress bars\n",
     "\n",
-    "shap.initjs()"
+    "shap.initjs()\n",
+    "\n",
+    "knn = sklearn.neighbors.KNeighborsClassifier()\n",
+    "knn.fit(X_train, Y_train)\n",
+    "\n",
+    "print_accuracy(knn.predict)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Explain a single prediction from the test set"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Using 120 background data samples could cause slower run times. Consider using shap.kmeans(data, K) to summarize the background as K weighted samples.\n"
+     ]
+    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy = 96.66666666666667%\n"
+      "<class 'shap.explainers.kernel.KernelExplainer'>\n"
      ]
     }
    ],
    "source": [
-    "knn = sklearn.neighbors.KNeighborsClassifier()\n",
-    "knn.fit(X_train, Y_train)\n",
-    "\n",
-    "print_accuracy(knn.predict)"
+    "explainer = KernelExplainer(knn.predict_proba, X_train)\n",
+    "print(type(explainer))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Using 120 background data samples could cause slower run times. Consider using shap.kmeans(data, K) to summarize the background as K weighted samples.\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n"
-     ]
-    },
     {
      "data": {
       "text/html": [
        "\n",
-       "<div id='iL6FNN4XCNZJJTJXVNAJW'>\n",
+       "<div id='iJ10F50N5ONS5UBVMDQU5'>\n",
        "<div style='color: #900; text-align: center;'>\n",
        "  <b>Visualization omitted, Javascript library not loaded!</b><br>\n",
        "  Have you run `initjs()` in this notebook? If this notebook was from another\n",
@@ -462,7 +436,7 @@
        " <script>\n",
        "   if (window.SHAP) SHAP.ReactDom.render(\n",
        "    SHAP.React.createElement(SHAP.AdditiveForceVisualizer, {\"outNames\": [\"output value\"], \"baseValue\": 0.3250000000000002, \"outValue\": 0.0, \"link\": \"identity\", \"featureNames\": [\"sepal length (cm)\", \"sepal width (cm)\", \"petal length (cm)\", \"petal width (cm)\"], \"features\": {\"0\": {\"effect\": -0.0012499999999999734, \"value\": 5.8}, \"1\": {\"effect\": -0.008750000000000036, \"value\": 2.8}, \"2\": {\"effect\": -0.2979166666666667, \"value\": 5.1}, \"3\": {\"effect\": -0.01708333333333345, \"value\": 2.4}}, \"plot_cmap\": \"RdBu\", \"labelMargin\": 20}),\n",
-       "    document.getElementById('iL6FNN4XCNZJJTJXVNAJW')\n",
+       "    document.getElementById('iJ10F50N5ONS5UBVMDQU5')\n",
        "  );\n",
        "</script>"
       ],
@@ -470,43 +444,33 @@
        "<IPython.core.display.HTML object>"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "shapexplainer = KernelExplainer(knn.predict_proba, X_train)\n",
-    "shap_values = shapexplainer.explain_instance(X_test.iloc[0,:])\n",
-    "shap.force_plot(shapexplainer.explainer.expected_value[0], shap_values[0], X_test.iloc[0,:])"
+    "# Shap original style for explaining input instances\n",
+    "shap_values = explainer.shap_values(X_test.iloc[0,:])\n",
+    "shap.force_plot(explainer.expected_value[0], shap_values[0], X_test.iloc[0,:])"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 11,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'aix360.algorithms.shap.shap_wrapper.KernelExplainer'>\n"
-     ]
-    }
-   ],
    "source": [
-    "print(type(shapexplainer))"
+    "### Explain all the predictions in the test set"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5bddb6f994cf4555a65eb30649cd650c",
+       "model_id": "236c4a11af794e15941943bac6ec73bf",
        "version_major": 2,
        "version_minor": 0
       },
@@ -517,74 +481,6 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -592,21 +488,11 @@
       "\n"
      ]
     },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n",
-      "/anaconda3/envs/aix360/lib/python3.6/site-packages/shap/explainers/kernel.py:555: UserWarning: l1_reg=\"auto\" is deprecated and in the next version (v0.29) the behavior will change from a conditional use of AIC to simply \"num_features(10)\"!\n",
-      "  \"l1_reg=\\\"auto\\\" is deprecated and in the next version (v0.29) the behavior will change from a \" \\\n"
-     ]
-    },
     {
      "data": {
       "text/html": [
        "\n",
-       "<div id='iIL1U0Z9OUJP2ECHBOB7G'>\n",
+       "<div id='i99VEWWC8CFDGLQESFS9Z'>\n",
        "<div style='color: #900; text-align: center;'>\n",
        "  <b>Visualization omitted, Javascript library not loaded!</b><br>\n",
        "  Have you run `initjs()` in this notebook? If this notebook was from another\n",
@@ -617,7 +503,7 @@
        " <script>\n",
        "   if (window.SHAP) SHAP.ReactDom.render(\n",
        "    SHAP.React.createElement(SHAP.AdditiveForceArrayVisualizer, {\"outNames\": [\"output value\"], \"baseValue\": 0.3250000000000002, \"link\": \"identity\", \"featureNames\": [\"sepal length (cm)\", \"sepal width (cm)\", \"petal length (cm)\", \"petal width (cm)\"], \"explanations\": [{\"outValue\": 0.0, \"simIndex\": 12.0, \"features\": {\"0\": {\"effect\": -0.0012499999999999734, \"value\": 5.8}, \"1\": {\"effect\": -0.008750000000000036, \"value\": 2.8}, \"2\": {\"effect\": -0.2979166666666667, \"value\": 5.1}, \"3\": {\"effect\": -0.01708333333333345, \"value\": 2.4}}}, {\"outValue\": 0.0, \"simIndex\": 29.0, \"features\": {\"0\": {\"effect\": 0.0, \"value\": 6.0}, \"1\": {\"effect\": 0.0, \"value\": 2.2}, \"2\": {\"effect\": -0.3250000000000002, \"value\": 4.0}, \"3\": {\"effect\": 0.0, \"value\": 1.0}}}, {\"outValue\": 1.0, \"simIndex\": 7.0, \"features\": {\"0\": {\"effect\": -0.000833333333333075, \"value\": 5.5}, \"1\": {\"effect\": 0.005833333333333635, \"value\": 4.2}, \"2\": {\"effect\": 0.6672222222222213, \"value\": 1.4}, \"3\": {\"effect\": 0.00277777777777799, \"value\": 0.2}}}, {\"outValue\": 0.0, \"simIndex\": 17.0, \"features\": {\"0\": {\"effect\": 0.0009722222222222077, \"value\": 7.3}, \"1\": {\"effect\": -0.0009722222222222077, \"value\": 2.9}, \"2\": {\"effect\": -0.32402777777777797, \"value\": 6.3}, \"3\": {\"effect\": -0.0009722222222222077, \"value\": 1.8}}}, {\"outValue\": 1.0, \"simIndex\": 8.0, \"features\": {\"0\": {\"effect\": -0.0012499999999996958, \"value\": 5.0}, \"1\": {\"effect\": 0.00458333333333355, \"value\": 3.4}, \"2\": {\"effect\": 0.6670833333333324, \"value\": 1.5}, \"3\": {\"effect\": 0.004583333333333606, \"value\": 0.2}}}, {\"outValue\": 0.0, \"simIndex\": 14.0, \"features\": {\"0\": {\"effect\": 0.0033333333333333826, \"value\": 6.3}, \"1\": {\"effect\": 0.0, \"value\": 3.3}, \"2\": {\"effect\": -0.32083333333333347, \"value\": 6.0}, \"3\": {\"effect\": -0.007500000000000062, \"value\": 2.5}}}, {\"outValue\": 1.0, \"simIndex\": 3.0, \"features\": {\"0\": {\"effect\": 0.00013888888888913264, \"value\": 5.0}, \"1\": {\"effect\": 0.0009722222222224297, \"value\": 3.5}, \"2\": {\"effect\": 0.6729166666666657, \"value\": 1.3}, \"3\": {\"effect\": 0.0009722222222225962, \"value\": 0.3}}}, {\"outValue\": 0.0, \"simIndex\": 30.0, \"features\": {\"0\": {\"effect\": 0.0, \"value\": 6.7}, \"1\": {\"effect\": 0.0, \"value\": 3.1}, \"2\": {\"effect\": -0.3250000000000002, \"value\": 4.7}, \"3\": {\"effect\": 0.0, \"value\": 1.5}}}, {\"outValue\": 0.0, \"simIndex\": 28.0, \"features\": {\"0\": {\"effect\": 0.0, \"value\": 6.8}, \"1\": {\"effect\": 0.0, \"value\": 2.8}, \"2\": {\"effect\": -0.3250000000000002, \"value\": 4.8}, \"3\": {\"effect\": 0.0, \"value\": 1.4}}}, {\"outValue\": 0.0, \"simIndex\": 27.0, \"features\": {\"0\": {\"effect\": 0.0, \"value\": 6.1}, \"1\": {\"effect\": 0.0, \"value\": 2.8}, \"2\": {\"effect\": -0.3250000000000002, \"value\": 4.0}, \"3\": {\"effect\": 0.0, 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\"features\": {\"0\": {\"effect\": 0.0005555555555555314, \"value\": 5.0}, \"1\": {\"effect\": -0.0038888888888888584, \"value\": 2.3}, \"2\": {\"effect\": -0.31833333333333347, \"value\": 3.3}, \"3\": {\"effect\": -0.0033333333333334103, \"value\": 1.0}}}, {\"outValue\": 1.0, \"simIndex\": 9.0, \"features\": {\"0\": {\"effect\": -0.0020833333333329374, \"value\": 5.0}, \"1\": {\"effect\": 0.0065277777777779655, \"value\": 3.4}, \"2\": {\"effect\": 0.6629166666666656, \"value\": 1.6}, \"3\": {\"effect\": 0.007638888888889195, \"value\": 0.4}}}], \"plot_cmap\": \"RdBu\", \"ordering_keys\": null, \"ordering_keys_time_format\": null}),\n",
-       "    document.getElementById('iIL1U0Z9OUJP2ECHBOB7G')\n",
+       "    document.getElementById('i99VEWWC8CFDGLQESFS9Z')\n",
        "  );\n",
        "</script>"
       ],
@@ -625,22 +511,16 @@
        "<IPython.core.display.HTML object>"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "shap_values = shapexplainer.explain_instance(X_test)\n",
-    "shap.force_plot(shapexplainer.explainer.expected_value[0], shap_values[0], X_test)"
+    "# Shap original style for explaining input instances\n",
+    "shap_values = explainer.shap_values(X_test)\n",
+    "shap.force_plot(explainer.expected_value[0], shap_values[0], X_test)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {