def testSetMaxDepth(self): maxDepth = 20 decisionTree = DecisionTree() decisionTree.setMaxDepth(maxDepth) decisionTree.learnModel(self.X, self.y) self.assertTrue(DecisionTree.depth(decisionTree.getClassifier().tree) <= maxDepth+1) maxDepth = 5 decisionTree = DecisionTree() decisionTree.setMaxDepth(maxDepth) decisionTree.learnModel(self.X, self.y) self.assertTrue(DecisionTree.depth(decisionTree.getClassifier().tree) <= maxDepth+1)
def testSetMaxDepth(self): maxDepth = 20 randomForest = RandomForest() randomForest.setMaxDepth(maxDepth) randomForest.learnModel(self.X, self.y) for c in randomForest.getClassifier().classifiers: self.assertTrue(DecisionTree.depth(c.tree) <= maxDepth+1) maxDepth = 5 randomForest = RandomForest() randomForest.setMaxDepth(maxDepth) randomForest.learnModel(self.X, self.y) for c in randomForest.getClassifier().classifiers: self.assertTrue(DecisionTree.depth(c.tree) <= maxDepth+1)
def testSetMaxDepth(self): maxDepth = 20 randomForest = RandomForest() randomForest.setMaxDepth(maxDepth) randomForest.learnModel(self.X, self.y) for c in randomForest.getClassifier().classifiers: self.assertTrue(DecisionTree.depth(c.tree) <= maxDepth + 1) maxDepth = 5 randomForest = RandomForest() randomForest.setMaxDepth(maxDepth) randomForest.learnModel(self.X, self.y) for c in randomForest.getClassifier().classifiers: self.assertTrue(DecisionTree.depth(c.tree) <= maxDepth + 1)
def testSetMaxDepth(self): maxDepth = 20 decisionTree = DecisionTree() decisionTree.setMaxDepth(maxDepth) decisionTree.learnModel(self.X, self.y) self.assertTrue( DecisionTree.depth(decisionTree.getClassifier().tree) <= maxDepth + 1) maxDepth = 5 decisionTree = DecisionTree() decisionTree.setMaxDepth(maxDepth) decisionTree.learnModel(self.X, self.y) self.assertTrue( DecisionTree.depth(decisionTree.getClassifier().tree) <= maxDepth + 1)