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| Pemungutan Suara Mayoritas× | Weighted Voting× | |
|---|---|---|
| Bidang≠ | Pembelajaran Ansambel | Pengambilan Keputusan |
| Keluarga≠ | Machine learning | MCDM |
| Tahun asal≠ | 1996 | 1951 |
| Pencetus≠ | Leo Breiman | Arrow, K. J. |
| Tipe≠ | voting aggregation | Social choice — weighted positional voting rule |
| Sumber perintis≠ | Breiman, L. (1996). Bagging predictors. Machine Learning, 24(2), 123-140. DOI ↗ | Arrow, K. J. (1951). Social Choice and Individual Values. Wiley, New York DOI ↗ |
| Alias≠ | hard voting | — |
| Terkait≠ | 5 | 0 |
| Ringkasan≠ | Majority voting is an ensemble method that combines predictions from multiple base classifiers by selecting the class that receives the most votes. Each base classifier casts one vote for a predicted class, and the final prediction is the class with the majority (plurality). This approach was formalized by Leo Breiman and colleagues in the 1990s as a simple yet effective way to improve classification accuracy. | WEIGHTED-VOTING (Weighted Voting — Weighted positional aggregation of multiple rankings) is a ranking multi-criteria decision-making (MCDM) method introduced by Arrow, K. J. in 1951. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
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