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

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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?

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