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HTM-MAT: An online prediction software toolbox based on cortical machine learning algorithm

Neural and Evolutionary Computing 2017-08-08 v1 Machine Learning

Abstract

HTM-MAT is a MATLAB based toolbox for implementing cortical learning algorithms (CLA) including related cortical-like algorithms that possesses spatiotemporal properties. CLA is a suite of predictive machine learning algorithms developed by Numenta Inc. and is based on the hierarchical temporal memory (HTM). This paper presents an implementation of HTM-MAT with several illustrative examples including several toy datasets and compared with two sequence learning applications employing state-of-the-art algorithms - the recurrentjs based on the Long Short-Term Memory (LSTM) algorithm and OS-ELM which is based on an online sequential version of the Extreme Learning Machine. The performance of HTM-MAT using two historical benchmark datasets and one real world dataset is also compared with one of the existing sequence learning applications, the OS-ELM. The results indicate that HTM-MAT predictions are indeed competitive and can outperform OS-ELM in sequential prediction tasks.

Keywords

Cite

@article{arxiv.1708.01659,
  title  = {HTM-MAT: An online prediction software toolbox based on cortical machine learning algorithm},
  author = {V. I. Anireh and EN Osegi},
  journal= {arXiv preprint arXiv:1708.01659},
  year   = {2017}
}

Comments

This research is currently under review in a Journal. Contents might vary from final published version

R2 v1 2026-06-22T21:07:24.663Z