[머신러닝] Decision Tree

Decision Tree

계속하여 이것인지 저것인지 결정한다.

from sklearn.preprocessing import StandardScaler

scaler = StandardScaler()

X = scaler.fit_transform(X)

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=3)

 

# 모델링

 

from sklearn.tree import DecisionTreeClassifier

classifier = DecisionTreeClassifier(random_state=3)

classifier.fit(X_train, y_train)

DecisionTreeClassifier(random_state=3)

 

y_pred = classifier.predict(X_test)

from sklearn.metrics import confusion_matrix, accuracy_score
cm = confusion_matrix(y_test, y_pred)

cm

array([[56,  9],
       [10, 25]], dtype=int64)​

accuracy_score(y_test, y_pred)

0.81