def testParallelPenaltyGrid(self): folds = 3 idx = Sampling.crossValidation(folds, self.X.shape[0]) decisionTree = DecisionTree() bestLearner, meanErrors = decisionTree.parallelVfcv(self.X, self.y, idx) trainX = self.X[0:40, :] trainY = self.y[0:40] paramDict = {} paramDict["setMinSplit"] = decisionTree.getMinSplits() paramDict["setMaxDepth"] = decisionTree.getMaxDepths() idealPenalties = decisionTree.parallelPenaltyGrid(trainX, trainY, self.X, self.y, paramDict)
def testParallelVfcv(self): folds = 3 idx = Sampling.crossValidation(folds, self.X.shape[0]) decisionTree = DecisionTree() bestLearner, meanErrors = decisionTree.parallelVfcv(self.X, self.y, idx)