Hybrid Feature Selection Algorithm for High Dimensional Database

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Provided by: International Journal of Engineering Trends and Technology
Topic: Big Data
Format: PDF
Feature subset selection is mainly applied to select the most important features from the original set of features. Feature subset selection is mainly calculated from the efficiency and effectiveness point of view. Feature subset selection is important in removing irrelevant and redundant features which reduces the dimensionality of data and is used to increase the understandability of the data which helps to avoid the slow performance of the algorithm. The FCBF (Fast Correlation Based Feature Selection) algorithm is implemented for the feature subset selection methods. The FAST algorithm is very much effective when compared with other algorithms. The FCBF is combined with the FAST algorithm to improve the efficiency of the FAST algorithm.
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