importnumpyasnpfromsklearn.svmimportsvcfromsklearnimportdatasetsfromsklearn.model _ selectionimporttrain _ test _ split irwiseimportrbf _ kernelimportmatplotlib.pyplotaspltfromsklearn.metrics.pai ics x，y=datasets.load _ breast _ cancanch y=datasets.make_blobs ) n_features=2，random_state=100 ) X_train，X_test，y_train，y _ test=test test_size=0.2 1)、c=y_train(#PLT.show )、m=x _ train.shape gamma=1/(d * x _ train.var ) ) model marker=' ^ ' (w=model.coef _ [0] print ('系数'，w ) PLT.Scatter ) w[1]，w[1]，s=120，c='r '，marker s=120，c='r '，marker=' ' ) PLT.show (ACC=accuracy _ score (y _ test，y_pred ) print ) '精度336033: -0.33918436 ) ) b=NP.Array(-2.21313321，-0.33918436 ) ) v=a-b print (cosine _ similarity ([ v ]，[w] ) )