D. Devakumari

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In feature selection, a search problem of finding a subset of features from a given set of measurements has been of interest for a long time. However, unsupervised methods are scarce. Examples of unsupervised methods include using the variance of data collected for each feature, or the projection of the feature on the first principal component. Another(More)
Feature subset selection is an essential task in data mining. This paper presents a new method for dealing with supervised feature subset selection based on Modified Fuzzy Relative Information Measure (MFRIM). First, Discretization algorithm is applied to discretize numeric features to construct the membership functions of each fuzzy sets of a feature. Then(More)
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