Python : 의사결정 나무

from sklearn.tree import DecisionTreeClassifier, plot_tree from sklearn.datasets import load_iris from sklearn.model_selection import train_test_split import warnings warnings.filterwarnings('ignore') # 붓꽃 데이터를 로딩하고, 학습과 테스트 데이터 셋으로 분리 iris_data = load_iris() X_train , X_test , y_train , y_test = train_test_split(iris_data.data, iris_data.target,test_size=0.2, random_state=11) # DecisionTree Classifier 생성 dt_clf = DecisionTreeClassifier(random_state=156, max_depth = 2) # DecisionTreeClassifer 학습...