A Review of Feature Selection Algorithms for Data Mining Techniques

Feature selection is a pre-processing step, used to improve the mining performance by reducing data dimensionality. Even though there exists a number of feature selection algorithms, still it is an active research area in data mining, machine learning and pattern recognition communities. Many feature selection algorithms confront severe challenges in terms of effectiveness and efficiency, because of recent increase in data dimensionality (data with thousands of features or attributes or variables). This paper analyses some existing popular feature selection algorithms, addresses the strengths and challenges of those algorithms.

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