Learning classifier system: Difference between revisions

Revision as of 12:06, 11 July 2017

Revision as of 12:53, 23 July 2017

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== Disadvantages ==

* Limited Software Availability: There are a limited number of open source, accessible LCS implementations, and even fewer that are designed to be user friendly or accessible to machine learning practitioners.

* Interpretation: While LCS algorithms are certainly more interpretable than some advanced machine learners, users must interpret a set of rules (sometimes large sets of rules to comprehend the LCS model. ). Methods for rule compaction, and interpretation strategies remains an area of active research.

* Theory/Convergence Proofs: There is a relatively small body of theoretical work behind LCS algorithms. This is likely due to their relative algorithmic complexity (applying a number of interacting components) as well as their stochastic nature.

* Overfitting: Like any machine learner, LCS can suffer from [[overfitting]] despite implicit and explicit generalization pressures.