A New Big Data Model Using Distributed Cluster-Based Resampling for Class-Imbalance Problem
The class imbalance problem, one of the common data irregularities, causes the development of under-represented models. To resolve this issue, the present study proposes a new cluster-based MapReduce design, entitled Distributed Cluster-based Resampling for Imbalanced Big Data (DIBID). The design ai...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2019-12-01
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| Series: | Applied Computer Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/acss-2019-0013 |