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About K-Nearest Algorithm Classification: Neighbor Based For Multi-Label
This document describes a k-nearest neighbor (kNN) based algorithm called ML-kNN for multi-label classification. ML-kNN identifies the k nearest neighbors of a test instance, determines the label sets of those neighbors, and uses maximum a posteriori (MAP) principle to predict the label set for the test instance. The document reviews previous work on multi-label learning and different evaluation criteria used to measure performance of multi-label classification algorithms.
Detailed Information
| Author: | ['Ethan Manani'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 4 |
| Language: | English |
| Format: | |
| Price: | FREE |
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