Fix test and appease Stan

Author: andrewdalpino

CHANGELOG.md

@@ -1,3 +1,6 @@
+- 2.5.1
+    - Fix bug in SVM (SVC and SVR) inferencing
+
 - 2.5.0
     - Added Vantage Point Spatial tree
     - Blob Generator can now `simulate()` a Dataset object

src/AnomalyDetectors/OneClassSVM.php

@@ -79,7 +79,6 @@ public function __construct(
             new ExtensionIsLoaded('svm'),
             new ExtensionMinimumVersion('svm', '0.2.0'),
         ])->check();
-        
 
         if ($nu < 0.0 or $nu > 1.0) {
             throw new InvalidArgumentException('Nu must be between'

src/Classifiers/AdaBoost.php

@@ -421,7 +421,7 @@ public function train(Dataset $dataset) : void
      * Make predictions from a dataset.
      *
      * @param Dataset $dataset
-     * @return list<string>
+     * @return list<int|string>
      */
     public function predict(Dataset $dataset) : array
     {

src/Datasets/Generators/Agglomerate.php

@@ -104,7 +104,7 @@ public function __construct(array $generators = [], ?array $weights = null)
         }
 
         $this->generators = $generators;
-        $this->weights = array_combine(array_keys($generators), $weights) ?: [];
+        $this->weights = array_combine(array_keys($generators), $weights);
         $this->dimensions = $dimensions;
     }
 

tests/AnomalyDetectors/OneClassSVMTest.php

@@ -7,7 +7,7 @@
 use Rubix\ML\Estimator;
 use Rubix\ML\EstimatorType;
 use Rubix\ML\Datasets\Unlabeled;
-use Rubix\ML\Kernels\SVM\Polynomial;
+use Rubix\ML\Kernels\SVM\RBF;
 use Rubix\ML\Datasets\Generators\Blob;
 use Rubix\ML\Datasets\Generators\Circle;
 use Rubix\ML\AnomalyDetectors\OneClassSVM;
@@ -43,7 +43,7 @@ class OneClassSVMTest extends TestCase
      *
      * @var float
      */
-    protected const MIN_SCORE = 0.5;
+    protected const MIN_SCORE = 0.7;
 
     /**
      * Constant used to see the random number generator.
@@ -77,7 +77,7 @@ protected function setUp() : void
             1 => new Circle(0.0, 0.0, 8.0, 1.0),
         ], [0.9, 0.1]);
 
-        $this->estimator = new OneClassSVM(0.01, new Polynomial(4, 1e-3), true, 1e-4);
+        $this->estimator = new OneClassSVM(0.3, new RBF(), true, 1e-4);
 
         $this->metric = new FBeta();
 
@@ -125,8 +125,8 @@ public function compatibility() : void
     public function params() : void
     {
         $expected = [
-            'nu' => 0.01,
-            'kernel' => new Polynomial(4, 1e-3),
+            'nu' => 0.3,
+            'kernel' => new RBF(),
             'shrinking' => true,
             'tolerance' => 0.0001,
             'cache size' => 100.0,

tests/NeuralNet/FeedForwardTest.php

@@ -86,7 +86,7 @@ public function build() : void
      */
     public function layers() : void
     {
-        $this->assertCount(7, $this->network->layers());
+        $this->assertCount(5, iterator_to_array($this->network->layers()));
     }
 
     /**