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Adjusting training set combination based on classification accuracy

Abstract:

Various embodiments are generally directed to techniques of adjusting the combination of the samples in a training batch or training set. Embodiments include techniques to determine an accuracy for each class of a classification model, for example. Based on the determined accuracies, the combination of the samples in the training batch may be adjusted or modified to improve the training of the classification model.