Comparison of a Classifier Performance Testing Methods: Support Vector Machine Classifier on Mammogram Images Classification


  • Thekra Hayder Abbas university, Baghdad,Iraq
  • Sura Jasim Mohammed university,Baghdad, Iraq



multiclass SVM, classifier test , cross-validation , hold-out


This paper compares between testing performance methods of classifier algorithm on a standard database of mammogram images. Mammographic interchange society dataset (MIAS) is used in this work. For classifying these images tumors a multiclass support vector machine (SVM) classifier is used. Evaluating this classifier accuracy for classifying the mammogram tumors into the malignant, benign or normal case is done using two evaluating classifier methods that are a hold-out method and one of the cross-validation methods. Then selecting the better test method depending on the obtained classifier accuracy and the running time consumed with each method. The classifier accuracy, training time and the classification time are considered for comparison purpose


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How to Cite

Abbas, T. H., & Mohammed, S. J. (2019). Comparison of a Classifier Performance Testing Methods: Support Vector Machine Classifier on Mammogram Images Classification. Journal of Kufa for Mathematics and Computer, 6(1).

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