Herein, theoretical results are presented to provide insights into the effectiveness of subsampling methods in reducing amount instances required training stage when applying support vector machines (SVMs) for classification big data scenarios. Our main theorem states that under some conditions, there exists, with high probability, a feasible solution SVM problem randomly chosen subsample, corr...