决策树对鸢尾花数据集进行分类

#!/usr/bin/python
# coding=utf-8
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeClassifier, export_graphviz
def dectree_demo():
    #决策树对鸢尾花数据集进行分类

    #获取数据
    iris = load_iris()

    #划分数据
    x_train, x_test, y_train, y_test = train_test_split(iris.data, iris.target)

    #决策树算法预估器
    estimator = DecisionTreeClassifier(criterion="entropy")
    estimator.fit(x_train, y_train)

    #模型评估
    y_predict = estimator.predict(x_test)
    print "y_predict:\n", y_predict
    print "对比真实值和预测值:\n", y_test == y_predict

    # 方法二：计算正确率
    score = estimator.score(x_test, y_test)
    print "准确率：\n", score

    #可视化决策树
    export_graphviz(estimator, out_file="iris_tree.dot", feature_names=iris.feature_names)
    return None

dectree_demo()