[Machine Learning] 분류 예측 Decision Tree

DecisionTreeClassifier() : 분할과 가지치기 과정을 반복 트리 기반의 분류 규칙을 만든다.

 

from sklearn.tree import DecisionTreeClassifier

>>> classifier = DecisionTreeClassifier(random_state=1)
>>> classifier.fit(X_train, y_train)

>>> y_pred = classifier.predict(X_test)
>>> y_pred
array([0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1,
       1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0,
       1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1,
       0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0,
       1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0], dtype=int64)
       
from sklearn.metrics import confusion_matrix, accuracy_score

>>> confusion_matrix(y_test, y_pred)
array([[50,  8],
       [ 8, 34]], dtype=int64)
       
>>> accuracy_score(y_test, y_pred)
0.84