Ejemplo de código sklearn.tree.DecisionTreeClassifier

Ejemplo 1: decisiontreeclassifier sklearn

from sklearn.tree import DecisionTreeClassifier

Ejemplo 2: decisión de aprender a dibujar

from sklearn.datasets import load_iris
from sklearn.tree import DecisionTreeClassifier
from sklearn.tree import export_text
iris = load_iris()
decision_tree = DecisionTreeClassifier(random_state=0, max_depth=2)
decision_tree = decision_tree.fit(iris.data, iris.target)
r = export_text(decision_tree, feature_names=iris['feature_names'])
print(r)

Ejemplo 3: criterio de gini del clasificador del árbol de decisiones de scikit

from sklearn.tree import DecisionTreeClassifier
from sklearn import metrics

# Max depth Decision tree classifier using gini criterion 

clf_gini_max = DecisionTreeClassifier(random_state=50, criterion='gini', max_depth=None)

clf_gini_max = clf_gini_max.fit(X_train,Y_train)
Y_pred = clf_gini_max.predict(X_test)

training_accuracy = clf_gini_max.score(X_train,Y_train)
testing_accuracy = clf_gini_max.score(X_test,Y_test)

print(training_accuracy)
print(testing_accuracy)

Ejemplo 4: árbol de decisiones de scikit learn

from sklearn import tree
X = [[0, 0], [1, 1]]
Y = [0, 1]
clf = tree.DecisionTreeClassifier()
clf = clf.fit(X, Y)

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