why do I have different results when i reuse the generated code from the classification learner app ?

1 次查看(过去 30 天)
Hello, I need some guide on how to reuse the generated code because it seems that i am making a mistake. I have used an input of 95x89 that i named it "trainerfeat" , where the 89's column is the response column,i fed this input to the app and chose 8% heldout validation , then i trained the data with svm and it turned out the the quadratic svm is the best and gives me 100% accuracy, then i chose generate the code option from the export model list and also chose the export model option. later, i have saved the generated code and saved the model as trainedclassifier4. then in the command line i wrote:
>> [trainedClassifier4, validationAccuracy] = trainClassifier(trainerfeat)
but it gives me different accuracy results !:
>> [trainedClassifier4, validationAccuracy] = trainClassifier(trainerfeat)
trainedClassifier4 =
predictFcn: @(x)svmPredictFcn(predictorExtractionFcn(x))
ClassificationSVM: [1x1 ClassificationECOC]
About: 'This struct is a trained classifier exported from Classification Learner R2016a.'
HowToPredict: 'To make predictions on a new predictor column matrix, X, use: …'
validationAccuracy =
0.5714
so can somebody tell me where i have gone wrong? any suggestions please?

回答(0 个)

类别

Help CenterFile Exchange 中查找有关 Classification Learner App 的更多信息

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by