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)
