3 examples of 'from sklearn.decision_tree import decisiontreeclassifier' in Python

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36def 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
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183def 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
41def __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)

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