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An ACO-ANN based feature selection algorithm for big data
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DOI：10.1007/s10586-018-2550-z.png)
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Abstract
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Feature selection is the approach of choosing subset of given dataset based on some feature. It can be used to minimize dimensions of the huge data set. So that it removes unnecessary data in the data source and produces prediction or output accurately in big data analytics. In the proposed work, feature selection algorithm process is implemented for text categorization using the algorithms ant colony optimization (ACO) and artificial neural network (ANN). This hybrid approach simulated using Reuter's data set and proved its efficiency.
Keywords:
Artificial neural network
Feature selection
Ant colony optimization
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