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Clustering Variation looks for a good subset of attributes in order to improve the classification accuracy of supervised learning techniques in classification problems with a huge number of attributes involved. It first creates a ranking of attributes based on the Variation value, then divide into two groups, last using Verification method to select the best group.
Features
- fast
- multiable class
- All kinds of attribute
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Machine LearningFollow Clustering Variation
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User Reviews
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Hi can I have the paper and more description about clustering Variation
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This Feature selection algorithm can choose better attribute from a dataset
