Merge pull request #1 from data-datum/master

Presentacion Into y clasificacion
data-datum · Sep 23, 2020 · 32c9b89 · 32c9b89
2 parents 6da8b25 + 8464ee1
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diff --git a/presentacion.Rmd → intro.Rmd b/presentacion.Rmd → intro.Rmd
diff --git a/intro.html b/intro.html
@@ -0,0 +1,195 @@
+<!DOCTYPE html>
+<html lang="" xml:lang="">
+  <head>
+    <title>Presentation Ninja</title>
+    <meta charset="utf-8" />
+    <meta name="author" content="Yihui Xie" />
+    <meta name="author" content="Garrick Aden-Buie" />
+    <meta name="date" content="2020-09-21" />
+    <script src="libs/xaringanExtra-logo/logo.js"></script>
+    <link rel="stylesheet" href="xaringan-themer.css" type="text/css" />
+  </head>
+  <body>
+    <textarea id="source">
+class: center, middle, inverse, title-slide
+
+# Presentation Ninja
+## ⚔️ xaringan +<br/>😎 xaringanthemer
+### Yihui Xie
+### Garrick Aden-Buie
+### 2020-09-21
+
+---
+
+
+
+
+
+
+
+
+<style type="text/css">
+.xaringan-extra-logo {
+  width: 110px;
+  height: 128px;
+  z-index: 0;
+  background-image: url('');
+  background-size: contain;
+  background-repeat: no-repeat;
+  position: absolute;
+  top:1em;right:1em;
+}
+</style>
+
+
+---
+
+
+# ¿Qué es el aprendizaje automático? 
+
+
+
+---
+
+# Aprendizaje automático e IA 
+
+
+
+---
+
+# El aprendizaje automático y otros campos relacionados
+
+---
+
+# IA y Ética
+
+
+---
+
+# El aprendizaje automático y ciencia de datos
+
+
+---
+    </textarea>
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diff --git a/libs/xaringanExtra-logo/logo.js b/libs/xaringanExtra-logo/logo.js
@@ -0,0 +1,14 @@
+
+(function() {
+let tries = 0
+function addLogo() {
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+    return
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+  	document.querySelectorAll('.remark-slide-content:not(.title-slide):not(.inverse):not(.hide_logo)')
+    	.forEach(el => el.innerHTML += '<div class="xaringan-extra-logo"></div>')
+  }
+}
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+})()
diff --git a/material/anexo/reg-logistica-RF.R b/material/anexo/reg-logistica-RF.R
@@ -7,10 +7,11 @@ library(palmerpenguins)
 penguins_df<-penguins %>%
   filter(!is.na(sex))%>%
   select(-year, -island)
-
+  
 library(tidymodels)
 library(ranger)
 set.seed(123)
+library(rsamples)
 penguin_split<-initial_split(penguins_df, strata=sex)
 penguin_train<-training(penguin_split)
 penguin_test<-testing(penguin_split)
@@ -54,7 +55,8 @@ rf_fit<-penguin_workf%>%
   )
 
 rf_fit
-rf_fit$metrics
+rf_fit$.metrics
+rf_fit$.predictions
 #roc curve y accuracy
 rf_fit %>%
   collect_metrics()
@@ -73,7 +75,7 @@ glm_fit %>%
   roc_curve(sex, .pred_female) %>%
   ggplot(aes(1 - specificity, sensitivity, color = id)) +
   geom_abline(lty = 2, color = "gray80", size = 1.5) +
-  geom_path(show.legend = FALSE, alpha = 0.6, size = 1.2) +
+  geom_path(show.legend = TRUE, alpha = 0.6, size = 1.2) +
   coord_equal()
 
 #random forest CURVA ROC
@@ -97,6 +99,7 @@ collect_metrics(penguin_final)
 collect_predictions(penguin_final) %>%
   conf_mat(sex, .pred_class)
 
+# PARA HACER
 install.packages("vip")
 library(vip)