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05 June 2018

Data obtained from clinical trials and healthcare can be of very high dimensions. The challenge is that the number of samples is usually a lot less compared to the number of features or the dimension of the data. In such a scenario, it is very important to choose the right subset of features to get predictive models with optimum performance. Genetic algorithm (GA) is a method of intelligently searching in this massive feature space. We give a brief introduction of the concept of GAs and then explain how it can be used for selection of features. We will also present some results obtained on using GAs for feature selection for a particular case study. 
 

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