alexa Abstract | A Survey on Feature Extraction Techniques
ISSN ONLINE(2320-9801) PRINT (2320-9798)

International Journal of Innovative Research in Computer and Communication Engineering
Open Access

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Research Article Open Access


Data Mining (DM) technique is able to process the high volume of data. The data mining applications contain dataset with high dimensionality. Due to this high dimensionality, the performance of the machine learning algorithms get degraded and this problem is resolved using a technique called Dimensionality Reduction (DR). DR is an essential preprocessing technique in DM to reduce the high dimensionality. Feature Extraction is one of the important techniques in DR to extract the most important features. The goal of this survey is to provide a comprehensive review of various feature extraction approaches to improve the classification accuracy. This paper gives an over view of various feature extraction techniques which are used to the budding researchers.

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Author(s): N. Elavarasan, Dr. K.Mani


Data Mining, Dimensionality Reduction, Feature Selection, Extraction Chromatography

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