一个处女座的程序猿

摘要： %RF：RF实现根据乳腺肿瘤特征向量高精度(better)预测肿瘤的是恶性还是良性 load data.mat a = randperm(569); Train = data(a(1:500),:); Test = data(a(501:end),:); P_train = Train(:,3:end); T_train = Train(:,2); P_test = Test(:,3:e... 阅读全文

摘要： %DT：DT实现根据乳腺肿瘤特征向量高精度预测肿瘤的是恶性还是良性 load data.mat a = randperm(569); Train = data(a(1:500),:); Test = data(a(501:end),:); P_train = Train(:,3:end); T_train = Train(:,2); P_test = Test(:,3:end); T_... 阅读全文

摘要： (1)导入数据：点击最左底部Import 按钮 (2)创建模型network_Jason_niu：点击底部的New按钮 (3)设置参数并训练：点击底部的Open按钮 (4)仿真预测： 大功告成！ 阅读全文

摘要： load iris_data.mat P_train = []; T_train = []; P_test = []; T_test = []; for i = 1:3 temp_input = features((i-1)*50+1:i*50,:); temp_output = classes((i-1)*50+1:i*50,:); n = randperm(50)... 阅读全文

摘要： %ELM：ELM基于近红外光谱的汽油测试集辛烷值含量预测结果对比—Jason niu load spectra_data.mat temp = randperm(size(NIR,1)); P_train = NIR(temp(1:50),:)'; T_train = octane(temp(1:50),:)'; P_test = NIR(temp(51:end),:)'; T_test ... 阅读全文

摘要： load concrete_data.mat n = randperm(size(attributes,2)); p_train = attributes(:,n(1:80))'; t_train = strength(:,n(1:80))'; p_test = attributes(:,n(81: 阅读全文

摘要： load BreastTissue_data.mat n = randperm(size(matrix,1)); train_matrix = matrix(n(1:80),:); train_label = label(n(1:80),:); test_matrix = matrix(n(81:end),:); test_label = label(n(81:end),:);... 阅读全文

摘要： load water_data.mat attributes = mapminmax(attributes); P_train = attributes(:,1:35); T_train = classes(:,1:35); P_test = attributes(:,36:end); T_test = classes(:,36:end); net = newc(minmax(P_t... 阅读全文

摘要： load water_data.mat attributes = mapminmax(attributes); P_train = attributes(:,1:35); T_train = classes(:,1:35); P_test = attributes(:,36:end); T_test = classes(:,36:end); net = newsom(P_tr... 阅读全文

摘要： load iris_data.mat P_train = []; T_train = []; P_test = []; T_test = []; for i = 1:3 temp_input = features((i-1)*50+1:i*50,:); temp_output = classes((i-1)*50+1:i*50,:); n = randperm(... 阅读全文