基于交叉svm分类的健康状态分类技术研究 基于交叉svm分类的健康状态分类技术研究 采取了交叉验证的方法优化SVM,并且对原

[{"title":"（ 16 个子文件 224KB ） 基于交叉svm分类的健康状态分类技术研究\n基于交叉svm分类的健康状态分类技术研究\n\n\n采取了交叉验证的方法优化SVM,并且对原","children":[{"title":"a1.m <span style='color:#111;'> 1.25KB </span>","children":null,"spread":false},{"title":"Copy_of_Untitled.m <span style='color:#111;'> 1.93KB </span>","children":null,"spread":false},{"title":"Copy_of_a1.m <span style='color:#111;'> 1.27KB </span>","children":null,"spread":false},{"title":"Outcome-Validation.xlsx <span style='color:#111;'> 10.09KB </span>","children":null,"spread":false},{"title":"model.mat <span style='color:#111;'> 15.45KB </span>","children":null,"spread":false},{"title":"Outcome-Training.xlsx <span style='color:#111;'> 10.07KB </span>","children":null,"spread":false},{"title":"4 Variables-Training.xlsx <span style='color:#111;'> 11.67KB </span>","children":null,"spread":false},{"title":"SVMcgForRegress.m <span style='color:#111;'> 1.29KB </span>","children":null,"spread":false},{"title":"scaleForSVM.m <span style='color:#111;'> 1.02KB </span>","children":null,"spread":false},{"title":"4 Variables-Validation.xlsx <span style='color:#111;'> 10.74KB </span>","children":null,"spread":false},{"title":"untitxxled1.fig <span style='color:#111;'> 11.04KB </span>","children":null,"spread":false},{"title":"AUC.m <span style='color:#111;'> 390B </span>","children":null,"spread":false},{"title":"新建 Microsoft Word 文档.docx <span style='color:#111;'> 184.43KB </span>","children":null,"spread":false},{"title":"Untitled3.m <span style='color:#111;'> 361B </span>","children":null,"spread":false},{"title":"untitxxled1.m <span style='color:#111;'> 7.69KB </span>","children":null,"spread":false},{"title":"Untitled.m <span style='color:#111;'> 1.93KB </span>","children":null,"spread":false}],"spread":true}]