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Implemented Multiclass Classifier using Support Vector Machine with the following datasets: Human Activity Datasets ----------------------- Number of classes: 6 Number of training data: 7352 Number of features: 561 Number of test data: 2947 VIdTIMIT Datasets ----------------------- Number of classes: 25 Number of training data: 3500 Number of features: 100 Number of test data: 1000 Handwritten Digits Datasets ----------------------- Number of classes: 10 Number of training data: 500 Number of features: 64 Number of test data: 3251 SVM is trained for each class, and for predicting a test sample, the maximum value returned by all the SVM are used to decide the final class.
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