Answers for "Build a decision tree classifier using scikit-learn's"

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scikit decision tree classifier gini criterion

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)

Posted by: Guest on November-08-2020

skit learn decision

import graphviz 
dot_data = tree.export_graphviz(clf, out_file=None) 
graph = graphviz.Source(dot_data) 
graph.render("iris")

Posted by: Guest on June-20-2020

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