Fast Parallel Constrained Viterbi Algorithm for Big Data with Applications to Financial Time Series

A new fast parallel constrained Viterbi algorithm for big data is proposed in this paper. We provide a detailed analysis of its performance on big data frameworks. This performance analysis includes the evaluation of execution time, speedup, and prediction accuracy. Additionally, we compare the impact of the proposed approach on the performance of our parallel constrained algorithm with other benchmark versions. We use synthetic data and...