decisiontreeregressor专题
(DecisionTreeRegressor)决策树回归预测实例-max_depth 学习笔记
import numpy as npfrom sklearn.tree import DecisionTreeRegressorimport matplotlib.pyplot as plt%matplotlib inlinen = 100x = np.random.rand(n)*6 - 3x.sort()y = np.sin(x) + np.random.rand(n) + 0.0
(DecisionTreeRegressor)决策树回归实例-加州房价数据 学习笔记
import matplotlib.pyplot as pltimport pandas as pdfrom sklearn.dataset.california_housing import fetch_california_housing# 读取加州房价数据housing = fetch_california_housing()#print(housing.DESCR)#housi