How To Draw The ROC Curve for SVM, KNN, & Naive Bayes Classifiers?

Hello, I'm not a professional MATLAB user, so I have some problem to find what I want. My problem is how can I draw the roc curve for SVM, KNN, & Naive Bayes Classifiers. For classification I use the "fit" to train my classifiers and "predict" to classify the test samples, and to find a roc curve I tried "plotroc" & "perfcurve", but without being able to draw curve. Can you Help me? I use MATLAB R2014a for information.

Answer 1

[Vladimir Calderón]

Load the sample data.

load ionosphere

X is a 351x34 real-valued matrix of predictors. Y is a character array of class labels: 'b' for bad radar returns and 'g' for good radar returns.

Reformat the response to fit a logistic regression. Use the predictor variables 3 through 34.

resp = strcmp(Y,'b'); % resp = 1, if Y = 'b', or 0 if Y = 'g'pred = X(:,3:34); 

Fit a logistic regression model to estimate the posterior probabilities for an iris to be a virginica.

mdl = fitglm(pred,resp,'Distribution','binomial','Link','logit'); score_log = mdl.Fitted.Probability; % Probability estimates

Compute the standard ROC curve using the probabilities for scores.

[Xlog,Ylog,Tlog,AUClog] = perfcurve(resp,score_log,'true'); 

Train an SVM classifier on the same sample data. Standardize the data.

mdlSVM = fitcsvm(pred,resp,'Standardize',true); 

Compute the posterior probabilities (scores).

mdlSVM = fitPosterior(mdlSVM); [~,score_svm] = resubPredict(mdlSVM); 

The second column of score_svm contains the posterior probabilities of bad radar returns.

Compute the standard ROC curve using the scores from the SVM model.

[Xsvm,Ysvm,Tsvm,AUCsvm] = perfcurve(resp,score_svm(:,mdlSVM.ClassNames),'true'); 

Fit a naive Bayes classifier on the same sample data.

mdlNB = fitcnb(pred,resp);

Compute the posterior probabilities (scores).

[~,score_nb] = resubPredict(mdlNB); 

Compute the standard ROC curve using the scores from the naive Bayes classification.

[Xnb,Ynb,Tnb,AUCnb] = perfcurve(resp,score_nb(:,mdlNB.ClassNames),'true'); 

Plot the ROC curves on the same graph.

plot(Xlog,Ylog) hold onplot(Xsvm,Ysvm) plot(Xnb,Ynb) legend('Logistic Regression','Support Vector Machines','Naive Bayes','Location','Best') xlabel('False positive rate'); ylabel('True positive rate'); title('ROC Curves for Logistic Regression, SVM, and Naive Bayes Classification') hold off

[Estefany Lancheros]

How To Draw The ROC Curve for KNN classifiers?

[Tianpei Li]

mdlknn = fitcknn(X,Y,'NumNeighbors',5,'Standardize',1)

[~,score_knn] = resubPredict(mdlknn);

[Xknn,Yknn,Tknn,AUCknn] = perfcurve(Y,score_knn(:,mdlknn.ClassNames),'true');

plot(Xknn,Yknn)

Answer 2

[SOLOMON Beyene]

I want to draw ROC curve for 6 algorithms(IBK,RF,ANN,KNN,J48,NB)

I have csv file with multclass..coulum contain features and rows contain class.

I am new user of Matlab ,can anyone help me how to load and draw in matlab