TWO-PHASE STACKING ENSEMBLE TO EFFECTIVELY HANDLE DATA IMBALANCES IN CLASSIFICATION PROBLEMS
Main Article Content
Abstract
Increase in generation of real-time data resulted in need of more processing requirements. However, processing of such data has several challenges associated with it. One of the major challenges in processing real-time data is to handle the implicit data imbalance. This paper proposes a two-phase stacking ensemble method to handle data imbalances more effectively during classification process. The proposed model utilizes multiple classifier algorithms in the first phase to predict data. The predicted data is used as input for the second phase. The second phase is a meta-learner, operating on predictions rather than the actual data. Experiments were conducted on data with varied imbalance levels. Obtained results indicate high efficiency of the proposed model in predicting with imbalanced data. A comparison with state-of-the-art model indicates improved performance.
Downloads
Download data is not yet available.
Article Details
Section
Articles
COPYRIGHT
Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
- The journal allows the author(s) to retain publishing rights without restrictions.
- The journal allows the author(s) to hold the copyright without restrictions.