Anyone help me please, How to use Classification Learner App to calculate accuracy rates on training set, and on test set??

I am using classification Learner App on my dataset. My dataset has two sets, Training set and Test set these sets are separate files, I have trained the training dataset using Classification learner and exported the model, now I am not getting how to evaluate this trained model on the test set, to check the accuracy on the test set too. Please help.

Answer 1

[Von Duesenberg]

It's all explained here: https://fr.mathworks.com/help/stats/export-classification-model-for-use-with-new-data.html Basically, if your trained model is called trainedModel, then use the predictFcn property on new data, eg.:

Y = trainedModel.predictFcn(newData)

[saeeda saher]

I tried this but did not get the confusion matrix and accuracy percentage the result is like following yfit = trainedModel.predictFcn(test)

yfit =

21×1 categorical array

     Surprise 
     Neutral 
     Sad 
     Disgust 
     Disgust 
     Disgust 
     Disgust 
     Disgust 
     Surprise 
     Sad 
     Fear 
     Sad 
     Angry 
     Happy 
     Angry 
     Disgust 
     Disgust 
     Neutral 
     Surprise 
     Fear 
     Surprise

[Von Duesenberg]

These are the predicted labels, you want now to use confusionmat or plotconfusion with true labels and predicted labels as arguments.

[kanuparthi bhagyasree]

Dear Saeeda saher,

I am also facing the same issue, I got the predicted labels but now I wanted to find the accuracy and confusion matrix for the test data.

How to do that?

Please help me.