A novel method of constrained feature selection by the measurement of pairwise constraints uncertainty

A novel method of constrained feature selection by the measurement of pairwise constraints uncertainty

Abstract In the past decades, the rapid growth of computer and database technologies has led to the rapid growth of large-scale datasets. On the other hand, data mining applications with high dimensional datasets that require high speed and accuracy are rapidly increasing. Semi-supervised learning i...

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Bibliographic Details
Main Authors: Mehrdad Rostami, Kamal Berahmand, Saman Forouzandeh
Format: Article
Language:English
Published: SpringerOpen 2020-10-01
Series:Journal of Big Data
Subjects:
Machine learning
Feature selection
Semi-supervised
Pairwise constraint
Uncertainty
Online Access:http://link.springer.com/article/10.1186/s40537-020-00352-3

Internet

http://link.springer.com/article/10.1186/s40537-020-00352-3

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