ML之DT：基于DT算法对titanic(泰坦尼克号)数据集乘客数据集进行二分类(是否获救)预测

ML之DT：基于DT算法对泰titanic(泰坦尼克号)数据集进行二分类(是否获救)预测

目录

输出结果

设计思路

核心代码

输出结果

设计思路

核心代码

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state = 33)

vec = DictVectorizer(sparse=False)    
X_train = vec.fit_transform(X_train.to_dict(orient='record'))
X_test = vec.transform(X_test.to_dict(orient='record'))


dtc = DecisionTreeClassifier()
dtc.fit(X_train, y_train)
y_predict = dtc.predict(X_test)
dtc.score(X_test, y_test))  
classification_report(y_predict, y_test, target_names = ['died', 'survived'])