A max-relevance-min-divergence criterion for data discretization with applications on naive Bayes
In many classification models, data is discretized to better estimate its distribution. Existing discretization methods often target at maximizing the discriminant power of discretized data, while overlooking the fact that the primary target of data discretization in classification is to improve the...
| Main Authors: | , , , , |
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| 其他作者: | |
| 格式: | Journal Article |
| 语言: | English |
| 出版: |
2024
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| 主题: | |
| 在线阅读: | https://hdl.handle.net/10356/180242 |