[PDF] Handling Sparse Data Sets by Applying Contrast Set Mining in ...
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H1: Contrast set mining techniques will perform feature selection on sparse data sets better than benchmarking feature selection techniques. H1.a. Contrast ...
contrast set mining techniques in feature selection on sparse data sets will result with more accurate classification than use of benchmarking feature ...
Results have shown superiority of contrast set mining techniques in more than 80% of the analysis on sparse data sets. This paper provides a study on the new ...
Handling Sparse Data Sets by Applying Contrast Set Mining in Feature Selection. January 2016; Journal of Software 11(2):148-161. DOI:10.17706/jsw.11.2.148-161.
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This paper proposes an efficient algorithm for incrementally mining frequent closed item sets without scanning the original database and searching the previous ...
Handling Sparse Data Sets by Applying Contrast Set Mining in Feature Selection. Dijana Oreški, Mario Konecki. 2016 Journal of Software. Preserved Fulltext.
In this paper, a novel graph-based sparse feature selection method is proposed that take into account both issues: relevancy and redundancy analysis.
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Jan 15, 2024 · We implement experiments on several real-world datasets and show that our method is fast in computation, clear in meaning, and offers a good ...
There also remains great potential for adaption of ECNN within other medical big data domains as a data mining tool for novel risk factor identification.
In this study, we propose an approach for feature selection for imbalanced data employing neighborhood rough set theory.