2. Matlab 2018a。 四、实验方法与流程 (1) 试验流程: Step1: 根据给定的数据,选定训练集和测试集; Step2: 为训练集与测试集选定标签集; Step3: 利用训练集进行训练分类器得到model; Step4: 根据model,对测试集进行测试集得到accuracy rate; (2)实验数据准备: 训练集:trainset(); 分别取bedroom(1:5,:)...
MATLAB中自带SVM包,使用起来也十分方便,假如X是特征矩阵,Y是分类标签(可以是数值(1、2)也可以是string,总之有区别就行。) 二分类代码 SVMModel=fitcsvm(X,y)%训练分类器CVSVMModel=crossval(SVMModel);%分类器的交叉验证classLoss=kfoldLoss(CVSVMModel)% 样本内错误率[~,score]=predict(SVMModel,X_test)%;...
function [model] = svmTrain(X, Y, C, kernelFunction, ... tol, max_passes) if ~exist('tol', 'var') || isempty(tol) tol = 1e-3; end if ~exist('max_passes', 'var') || isempty(max_passes) max_passes = 5; end % Data parameters m = size(X, 1); n = size(X, 2);...
4 训练好的 model贮存与使用save example1 model%将训练好的model储存为example1load example1.mat 注意事项 matlab对libsvm配置后，自带函数应该不能使用了，help svmtrain为libsvm中的帮助文件
K = kernel_matrix2(omega,model.kernel_type,model.kernel_pars,d); Atot = K+Inb./model.gam; % Cholesky factor try R = chol(Atot); % Solve full system q = R\(R'\[py S]); p = q(:,2); q = q(:,1); s = 1/sum(p); ...
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how i can calculate accuraccy of svm model for multiple class,for one vs all classifier, i calculate the maximum score of the tested data, 댓글 수: 0 댓글을 달려면 로그인하십시오. 답변 (1개) Hari2023년 9월 5일 ...
model= svmtrain(trainlabel,traindatak,cmd); 3、 遇到的问题 A 分类模型 多分类(单个模型): 我要做的是不同人的身份识别,比如我现在有20个人的数据,我需要识别出这20个人,这样一看好像就是个多分类问题,一个多分类模型就可以搞定,我也用了一些matlab中自带的一个应用于多分类的svm(这个在2014版以后的matl...
model=svmtrain(train_label,train,'-c 2 -g 0.01'); [predict_label,accuracy]=svmpredict(test_label,test,model); 错误记录 1 make这一步报错 Error using mex (line 206) Unable to complete successfully. Error in make (line 1) % This make.m is for MATLAB and OCTAVE ...
fitrsvm trains or cross-validates a support vector machine (SVM) regression model on a low- through moderate-dimensional predictor data set.