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cs.LG2020★ 2 cited
tsBNgen: A Python Library to Generate Time Series Data from an Arbitrary Dynamic Bayesian Network Structure
Manie Tadayon, Greg Pottie
Synthetic data is widely used in various domains. This is because many modern algorithms require lots of data for efficient training, and data collection and labeling usually are a…
cs.LG2020★ 3 cited
Comparative Analysis of the Hidden Markov Model and LSTM: A Simulative Approach
Manie Tadayon, Greg Pottie
Time series and sequential data have gained significant attention recently since many real-world processes in various domains such as finance, education, biology, and engineering c…
cs.LG2020
A clustering approach to time series forecasting using neural networks: A comparative study on distance-based vs. feature-based clustering methods
Manie Tadayon, Yumi Iwashita
Time series forecasting has gained lots of attention recently; this is because many real-world phenomena can be modeled as time series. The massive volume of data and recent advanc…