A Study on Classifiers for Temporal Data
Brijendra Singh, Rashi Jaiswal · 2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT) · 2022
Various researchers have developed the several classifiers to perform the classification task on data to get the specified information. The temporal information classification task is so challenging due to time dependency. In this paper, we have studied various classifiers for temporal data processing and performed the empirical study on different temporal datasets to explore the probability of best classifiers to solve the classification problems. This paper also performed the analysis on classifiers with categorized them into the traditional and advanced classifiers to investigate the various quantitative parameters (i.e. accuracy and execution time, etc.) as well as qualitative parameters (i.e. space complexity, etc.). That is required to evaluate the classifiers performance and importance through experimental study. This paper provides the direction of the future research problems that help to various researchers and scientists for exploration of other methods to create the solutions for data classification.