#encoding=utf-8
import numpy as np
import pandas as pd

def main():
    from sklearn.datasets import load_iris
    iris=load_iris()
    print(iris)

    print(len(iris["data"]))
    from sklearn.model_selection import train_test_split
    #分成测试和验证数据集，比例是0.2
    train_data,test_data,train_target,test_target=train_test_split(iris.data,iris.target,test_size=0.2,random_state=1)

    #Model
    from sklearn import tree
    clf=tree.DecisionTreeClassifier(criterion="entropy")
    clf.fit(train_data,train_target)
    y_pred=clf.predict(test_data)

    #Verify
    from sklearn import metrics
    print(metrics.accuracy_score(y_true=test_target,y_pred=y_pred))
    print(metrics.confusion_matrix(y_true=test_target,y_pred=y_pred))

    #输出结果
    with open("./data/tree.dot","w") as fw:
        tree.export_graphviz(clf,out_file=fw)

if __name__ == '__main__':
    main()