MATLAB: Classification learner – identify false prediction indexes

classification learnerStatistics and Machine Learning Toolbox

In classification learner app, after training a model, how to identify the indexes (in feature table) of false predictions?

Best Answer

Unfortunately, that isn't supported directly in the Classification Learner. But you can export your trained model to the MATLAB workspace, predict on a set of held-out data there, and identify which observations were misclassified.

Related Solutions

MATLAB: The SVM classifier embebed in classfication learner App can do multiclass classification or not

Hi Frank,

"In Classification Learner, you can train SVMs when your data has two or more classes."

You can refer to the following documentation to know more about SVM classifier in classification learner app:

https://www.mathworks.com/help/stats/choose-a-classifier.html#bunt0n0-1

Hope it helps!

MATLAB: How to get prediction scores from exported Classification Learner SVM model

Hello Ashley,

The predict function expects an input classifier of type such as ClassificationKNN or ClassificationTree etc. In this case you are passing a variable T which is if type struct. That is the reason for the error.

Type the following at the command prompt to see the contents of the struct:

>> T %Variable name of the exported classifier struct

Here one of the fields will be the classification object. For e.g. for my exported model referred by struct variable trainedClassifier, I see the following.

>> trainedClassifier
trainedClassifier = 
           predictFcn: [function_handle]
    RequiredVariables: {1x11 cell}
    ClassificationKNN: [1x1 ClassificationKNN]
                About: 'This struct is a tra…'
         HowToPredict: 'To make predictions …'

Note here that one of the fields is the actual classification object, ClassificationKNN. Note that, based on the type of trained classifier this might differ. To access this we can use the dot operator.

kNNMdl = trainedClassifier.ClassificationKNN;

Now use this as input to the predict function to get scores:

[labels,score] = predict(kNNMdl,ValData);

Best Answer

Related Solutions

MATLAB: The SVM classifier embebed in classfication learner App can do multiclass classification or not

MATLAB: How to get prediction scores from exported Classification Learner SVM model

Related Question