When To Use Genetic Algorithm For Data Mining Task?

You already got model(s) for your data but not sure whether the models are accurate enough for predictive data mining. Well, one of the way you can optimize your predictive model is through the use of Genetic Algorithm (one of the application of evolutionary computation). According to Wikipedia:

A genetic algorithm (GA) is a search technique used in computing to find exact or approximate solutions to optimization and search problems. Genetic algorithms are categorized as global search heuristics. Genetic algorithms are a particular class of evolutionary algorithms (EA) that use techniques inspired by evolutionary biology such as inheritance, mutation, selection, and crossover.

Currently, genetic algorithms find application in bioinformatics, phylogenetics, computational science, engineering, economics, chemistry, manufacturing, mathematics,physics and other fields.

Read white paper about how to “Using Genetic Algorithms for Parameter Optimization in Building Predictive Data Mining Models“, which describes the problem of finding optimal predictive model building parameter as an optimization problem and examine the usefulness of genetic algorithms. They perform experiments on several datasets and report empirical results to show the applicability of genetic algorithms to the problem of finding optimal predictive model building parameters.

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