ML之分类预测:基于sklearn库的七八种机器学习算法利用糖尿病(diabetes)数据集(8→1)实现二分类预测
目录
k-NN:Accuracy of K-NN classifier on training set: 0.79
k-NN:Accuracy of K-NN classifier on test set: 0.78
LoR:C1 Training set accuracy: 0.781
LoR:C1 Test set accuracy: 0.771
LoR:C100 Training set accuracy: 0.785
LoR:C100 Test set accuracy: 0.766
LoR:C001 Training set accuracy: 0.700
LoR:C001 Test set accuracy: 0.703
DT:Accuracy on training set: 1.000
DT:Accuracy on test set: 0.714
DT:Accuracy on training set: 0.773
DT:Accuracy on test set: 0.740
RF:Accuracy on training set: 1.000
RF:Accuracy on test set: 0.786
RF:max_depth=3 Accuracy on training set: 0.800
RF:max_depth=3 Accuracy on test set: 0.755
GB:Accuracy on training set: 0.917
GB:Accuracy on test set: 0.792
GB:Accuracy on training set: 0.804
GB:Accuracy on test set: 0.781
GB:Accuracy on training set: 0.802
GB:Accuracy on test set: 0.776
SVM:Accuracy on training set: 1.00
SVM:Accuracy on test set: 0.65
SVM:MinMaxScaler Accuracy on training set: 0.77
SVM:MinMaxScaler Accuracy on test set: 0.77
SVM:C=500 Accuracy on training set: 0.790
SVM:C=500 Accuracy on test set: 0.792
SVM:C=1000 Accuracy on training set: 0.790
SVM:C=1000 Accuracy on test set: 0.797
SVM:C=2000 Accuracy on training set: 0.800
SVM:C=2000 Accuracy on test set: 0.797
利用多层神经网络
NN:Data standardization—Accuracy on training set: 0.823
NN:Data standardization—Accuracy on test set: 0.802
NN:Data standardization(max_iter=1000)—Accuracy on training set: 0.877
NN:Data standardization(max_iter=1000)—Accuracy on test set: 0.755
NN:Data standardization(max_iter=1000,alpha=1)—Accuracy on training set: 0.795
NN:Data standardization(max_iter=1000,alpha=1)—Accuracy on test set: 0.792
相关文章
ML之Classification:基于sklearn库的七八种机器学习算法利用糖尿病(diabetes)数据集(8→1)实现二分类预测
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