使用回归树进行波士顿房价的预测并且可视化树的结构

本文主要实现使用回归决策树对波士顿房价的预测

#使用boston房价预测练习回归树的建模
import pandas as pd
from sklearn import preprocessing
from sklearn import tree
from sklearn.datasets import load_boston
boston_house=load_boston()
#加载数据
boston_features_name=boston_house.feature_names
boston_features=boston_house.data
boston_taget=boston_house.target
#构建模型
rgs=tree.DecisionTreeRegressor(max_depth=4)
rgs=rgs.fit(boston_features,boston_taget)
print(rgs)
import pydotplus
from IPython.display import Image,display
dot_data=tree.export_graphviz(rgs,
               out_file=None,
               feature_names=boston_features_name,
               class_names=boston_taget,
               filled=True,
               rounded=True
               )
graph=pydotplus.graph_from_dot_data(dot_data)
display(Image(graph.create_png()))

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