from sklearn.datasets import load_iris iris = load_iris() 波士顿房价数据集 (Boston Housing Dataset) 描述:该数据集包含波士顿地区506个房屋的13个特征,以及这些房屋的中位数房价。特征包括犯罪率、住宅用地比例、非零售商业用地比例、氮氧化物浓度、平均房间数、房龄、距离就业中心的距离、公路通达性、财产税率...
Ames housing dataset. You can load the datasetsasfollows::fromsklearn.datasets import fetch_california_housing housing=fetch_california_housing()forthe California housing dataset and::fromsklearn.datasets import fetch_openml housing= fetch_openml(name="house_prices", as_frame=True)forthe Ames housi...
from sklearn.datasets import load_boston from sklearn.ensemble import RandomForestRegressor #Load boston housing dataset as an example boston = load_boston() X = boston["data"] Y = boston["target"] names = boston["feature_names"] rf = RandomForestRegressor(n_estimators=20, max_depth=4) ...
#import boston housing dataset import pandas as pd import numpy as np from sklearn.model_selection import train_test_split from sklearn.datasets import load_boston from sklearn.ensemble import RandomForestRegressor #load boston data boston = load_boston() boston; #create boston_df1 DataFrame bosto...
from sklearn.datasetsimportload_boston from sklearn.ensembleimportRandomForestRegressor#Load boston housing datasetasan example boston=load_boston()X=boston["data"]Y=boston["target"]names=boston["feature_names"]rf=RandomForestRegressor(n_estimators=20,max_depth=4)scores=[]foriinrange(X.shape[1]...
sklearn.feature_selection.VarianceThreshold(threshold=0.0) 参数: threshold: 指定方差的阙值,特征的方差低于此阙值将被剔除 成员属性: variances_:一个数组,分别为各特征的方差 成员方法: fit(X,[,y]):从样本数据中学习方差 transform(X): 执行特征选择(删除低于阙值的特征) ...
我们可以清楚地看到,scikit-learn的LinearRegression模型比OpenCV的fitLine函数执行结果更好。现在,让我们使用scikit-learn的API来预测波士顿的房价。 3.4.3 使用线性回归预测波士顿房价 为了更好地理解线性回归,我们想构建一个简单模型,可应用于一个最著名的机器学习数据集:波士顿房价数据集(Boston housing prices dataset)...
`load_boston` has been removed from scikit-learn since version 1.2. The Boston housing prices dataset has an ethical problem: as investigated in [1], the authors of this dataset engineered a non-invertible variable "B" assuming that racial self-segregation had a ...
scikit-learn california housing dataset cal_housing.tgzNelson, Liu
>>>data,target=load_boston(return_X_y=True) 2. 真实数据集 这里的真实数据集也是经典的数据集之一,只不过数据量较大,所以没有内置在模块中,采用了从网络上下载的方式,对于回归算法而言,有以下加载函数 1. fetch_california_housing() 对于分类算法而言,有以下加载函数 ...