Multi-view Genetic Programming Learning to Obtain Interpretable Rule-Based Classifiers for Semi-supervised Contexts. Lessons Learnt
Carlos García‐Martínez, Sebastián Ventura · International Journal of Computational Intelligence Systems · 2020
Multi-view learning analyzes the information from several perspectives and has largely been applied on semi-supervised contexts.It has not been extensively analyzed for inducing interpretable rule-based classifiers.We present a multi-view and grammarbased genetic programming model for inducing rules for semi-supervised contexts.It evolves several populations and views, and promotes both accuracy and agreement among the views.This work details how and why common practices may not produce the expected results when inducing rule-based classifiers under this methodology.