def testSetMaxDepth(self):
maxDepth = 20
randomForest = RandomForest()
randomForest.setMaxDepth(maxDepth)
randomForest.learnModel(self.X, self.y)
#self.assertTrue(RandomForest.depth(randomForest.getClassifier().tree) <= maxDepth+1)
maxDepth = 5
randomForest = RandomForest()
randomForest.setMaxDepth(maxDepth)
randomForest.learnModel(self.X, self.y)
def testSetMaxDepth(self):
maxDepth = 20
randomForest = RandomForest()
randomForest.setMaxDepth(maxDepth)
randomForest.learnModel(self.X, self.y)
#self.assertTrue(RandomForest.depth(randomForest.getClassifier().tree) <= maxDepth+1)
maxDepth = 5
randomForest = RandomForest()
randomForest.setMaxDepth(maxDepth)
randomForest.learnModel(self.X, self.y)
def testSetWeight(self):
#Try weight = 0 and weight = 1
randomForest = RandomForest()
randomForest.setWeight(0.0)
randomForest.learnModel(self.X, self.y)
predY = randomForest.predict(self.X)
self.assertTrue((predY == numpy.zeros(predY.shape[0])).all())
randomForest.setWeight(1.0)
randomForest.learnModel(self.X, self.y)
predY = randomForest.predict(self.X)
self.assertTrue((predY == numpy.ones(predY.shape[0])).all())
def testSetWeight(self):
#Try weight = 0 and weight = 1
randomForest = RandomForest()
randomForest.setWeight(0.0)
randomForest.learnModel(self.X, self.y)
predY = randomForest.predict(self.X)
self.assertTrue((predY == numpy.zeros(predY.shape[0])).all())
randomForest.setWeight(1.0)
randomForest.learnModel(self.X, self.y)
predY = randomForest.predict(self.X)
self.assertTrue((predY == numpy.ones(predY.shape[0])).all())
def testPredict(self):
randomForest = RandomForest()
randomForest.learnModel(self.X, self.y)
predY = randomForest.predict(self.X)
inds = numpy.random.permutation(self.X.shape[0])
predY2 = randomForest.predict(self.X[inds, :])
self.assertTrue((predY[inds] == predY2).all())
#Let's test on -1, +1 labels
y2 = (self.y * 2) - 1
randomForest.learnModel(self.X, y2)
predY2 = randomForest.predict(self.X)
self.assertTrue((predY2 == predY * 2 - 1).all())
def testPredict(self):
randomForest = RandomForest()
randomForest.learnModel(self.X, self.y)
predY = randomForest.predict(self.X)
inds = numpy.random.permutation(self.X.shape[0])
predY2 = randomForest.predict(self.X[inds, :])
self.assertTrue((predY[inds] == predY2).all())
#Let's test on -1, +1 labels
y2 = (self.y*2)-1
randomForest.learnModel(self.X, y2)
predY2 = randomForest.predict(self.X)
self.assertTrue((predY2 == predY*2-1).all())
def testLearnModel(self):
randomForest = RandomForest()
randomForest.learnModel(self.X, self.y)
tree = randomForest.getClassifier()
def testLearnModel(self):
randomForest = RandomForest()
randomForest.learnModel(self.X, self.y)
tree = randomForest.getClassifier()
