期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2017
卷号：6
期号：9
页码：18629
DOI：10.15680/IJIRSET.2017.0609161
出版社：S&S Publications
摘要：In present, duplicate detection methods need to process ever larger datasets in ever shorter time,maintaining the quality of a dataset becomes increasingly difficult. Feature selection plays a significant role inimproving the performance of the machine learning algorithms in terms of reducing the time to build the learningmodel and increasing the accuracy in the learning process. Therefore, the researchers pay more attention on the featureselection to enhance the performance of the machine learning algorithms. Identifying the suitable feature selectionmethod is very essential for a given machine learning task with high-dimensional data. Hence, it is required to conductthe study on the various feature selection methods for the research community especially dedicated to develop thesuitable feature selection method for enhancing the performance of the machine learning tasks on high-dimensionaldata. In order to fulfill this objective, this paper devotes the complete literature review on the various feature selectionmethods for high-dimensional data..
