1.导入相应包from sklearn.datasets import load_breast_cancerfrom sklearn.svm import SVCfrom sklearn.model_selection import train_test_splitimport matplotlib.pyplot as pltimport numpy as npfrom time import t

在学习完吴恩达老师的机器学习教程后，开始在B站学习菜菜的sklearn机器学习视频。1.导入相应包以及红酒数据集from sklearn import treefrom sklearn.datasets import load_winefrom sklearn.model_selection import train_test_split2.查看红酒数据集中的数据wine = load_wine(

1.导入相应包import pandas as pdimport numpy as npimport matplotlib.pyplot as pltfrom sklearn.model_selection import train_test_split2.读取数据集并分析weather = pd.read_csv(r"D:\download\sklearnjqxx_jb51\【机器学习】菜菜的s

1.导入相应包from sklearn.datasets import fetch_lfw_peoplefrom sklearn.decomposition import PCAfrom matplotlib import pyplot as pltimport pandas as pdimport numpy as np2.准备数据集本次我们使用的数据集是sklearn库中自带的人脸图片数据集，

1.导入相应包from sklearn.datasets import make_blobsfrom sklearn.svm import SVCfrom matplotlib import pyplot as pltimport numpy as npimport pandas as pd%matplotlib inline2.准备数据集并可视化X, y = make_blobs(n_sampl

1.导入相应包import pandas as pdfrom sklearn.tree import DecisionTreeClassifierfrom sklearn.model_selection import train_test_splitfrom sklearn.model_selection import GridSearchCVfrom sklearn.model_selectio