Presorted Tsetlin Machine The Genetic Kmedoid Method

# Pre-Sorted Tsetlin Machine (The Genetic K-Medoid Method)

**arXiv ID:** 2403.09680
**Authors:** Jordan Morris
**Published:** 2024-02-07T15:30:23Z
**Abstract:**
This paper proposes a machine learning pre-sort stage to traditional supervised learning using Tsetlin Machines. Initially, K data-points are identified from the dataset using an expedited genetic algorithm to solve the maximum dispersion problem. These are then used as the initial placement to run the K-Medoid clustering algorithm. Finally, an expedited genetic algorithm is used to align K independent Tsetlin Machines by maximising hamming distance. For MNIST level classification problems, results demonstrate up to 10% improvement in accuracy, approx. 383X reduction in training time and approx. 86X reduction in inference time.

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## References

- [arXiv:2403.09680](http://arxiv.org/abs/2403.09680v2)