This study demonstrates the potential of genetic programming (GP) as a base classifier algorithm in building ensembles in the context of large-scale data classification. An ensemble built upon base classifiers that were trained with GP was found to significantly outperform its counterparts built upon base classifiers that were trained with decision tree and logistic regression. The superiority of GP ensembles is attributed to the higher diversity, both in terms of the functional form of as well as with respect to the variables defining the models, among the base classifiers. Keywords: Genetic Programming, Ensemble, Classification, Large Scale Data Please do not quote without permission.
In REF authors demonstrated the suitability of GP as a base classifier algorithm in building ensembles for large-scale data classification.
Genetic programming in classifying large-scale data: an ensemble method
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Computer Science