1、鸢尾花SVM特征分类: plt.subplot(221)## 区域图plt.pcolormesh(x1,x2,svm_grid_hat,cmap=cm_light)## 所以样本点plt.scatter(x[0],x[1],c=y,edgecolors='k',s=50,cmap=cm_dark)# 样本## 测试数据集plt.scatter(x_test[0],x_test[1],s=120,facecolors='none',zorder=10)# 圈中测试集...
importnumpyasnpimportpandasaspdimportmatplotlibasmplimportmatplotlib.pyplotaspltimportwarningsfromsklearnimportsvm#svm导入fromsklearn.svmimportSVCfromsklearn.model_selectionimporttrain_test_splitfromsklearn.metricsimportaccuracy_scorefromsklearn.exceptionsimportChangedBehaviorWarning 案例二 - 鸢尾花数据不同分类器效...
fromsklearnimportdatasets #一、数据的获取 iris=datasets.load_iris() #df=pd.DataFrame(iris.data,columns=iris.feature_names) #df['target']=iris.target #plt.plot(df) #plt.show() #二、数据预处理 fromsklearnimportpreprocessing scaler=preprocessing.MinMaxScaler()#MinMaxScaler将样本特征值线性缩放到0.1...