Empirical Evaluation of Deep Learning based Models for Time Series Datasets
Malav Champaneria, Dhyani Panchal, Jiten Bhalavat, Hemant N. Yadav, Nirav Bhatt, Nirav Bhatt, Purvi Prajapati, Nikita Bhatt, Nikita Bhatt · Procedia Computer Science · 2023
A deep learning-based method for predicting numerous time series is suggested in this study. For example, this paper contrasts the effectiveness of DeepAR, N- Beats, Transformer, Temporal Fusion Transformer, and other deep learning models. Our test findings demonstrate that deep learning models can anticipate with excellent accuracy across a variety of time series datasets. Moreover, our results indicate that the ideal input representation differs among datasets and that it plays a significant impact in predicting accuracy. Overall, our work gives practical advice for choosing the appropriate model and input representation, as well as insights into the use of deep learning models for predicting numerous time series.