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

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

输出结果

数据集展示

输出结果

1、k-NN

2、LoR

4、DT

5、RF

6、GB

​​​7、SVM

8、NN

设计思路

 

 

输出结果 数据集展示

输出结果 1、k-NN

k-NN：Accuracy of K-NN classifier on training set: 0.79 k-NN：Accuracy of K-NN classifier on test set: 0.78

 

2、LoR

#  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

  4、DT

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

  5、RF

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

  6、GB

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

 

7、SVM

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

 

 

8、NN

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

 

 

设计思路

 

 

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