Big data classification with quantum multiclass SVM and quantum one-against-all approach

In this paper, we have proposed a quantum approach for multiclass support vector machines to handle big data classification. To achieve this goal, we have also developed and implemented a quantum version of the one-against-all algorithm. The proposed approach demonstrates that the big data multiclass classification can be implemented with quantum multiclass support vector machine in logarithmic time complexity on a quantum computer, compared to the classical multiclass support vector machines that can be implemented with polynomial time complexity. Hence, our proposed approach exhibits an exponential speed up in time complexity for big data multiclass classification.