3 examples of 'from sklearn.decision_tree import decisiontreeclassifier' in Python
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36 def decisiontree(data): 37 Xt = [] 38 Yt = [] 39 Xv = [] 40 Yv = [] 41 # Adds 90% of the data to the trainingsset, 10% to the validationset. 42 np.random.shuffle(data) 43 trainingsize = 0.9 * len(data) 44 training = data[:int(trainingsize)] 45 validation = data[int(trainingsize):] 46 47 # Creates the X and Y parts of the training and test sets. 48 # Also fills the tree species list (classes) with all different species. 49 for line in training: 50 if line[-1] not in classes: 51 classes.append(line[-1]) 52 Xt.append(line[0:-1]) 53 Yt.append(line[-1]) 54 for line in validation: 55 if line[-1] not in classes: 56 return decisiontree(data) 57 Xv.append(line[0:-1]) 58 Yv.append(line[-1]) 59 60 clf = tree.DecisionTreeClassifier() 61 clf = clf.fit(Xt, Yt) 62 return clf, Xt, Yt, Xv, Yv
183 def predict(self, X): 184 predictions = np.zeros(X.shape[0]) 185 for i, observation in enumerate(X): 186 predictions[i] = self.single_prediction(observation, self.root) 187 return predictions
41 def __init__(self, classes): 42 """ 43 Constructor 44 :param classes: Classes 45 :param lang: Spacy language 46 """ 47 super(DecisionTree, self).__init__(classes) 48 # Properties 49 self._token2index = dict() 50 self._voc_size = 0 51 self._samples = list() 52 self._n_samples = 0 53 self._tree_classifier = DecisionTreeClassifier(random_state=0)