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mlquantify

Algorithms for Class Distribution Estimation

v0.2.0 · Jan 20, 2022 · GPL (>= 2.0)

Description

Quantification is a prominent machine learning task that has received an increasing amount of attention in the last years. The objective is to predict the class distribution of a data sample. This package is a collection of machine learning algorithms for class distribution estimation. This package include algorithms from different paradigms of quantification. These methods are described in the paper: A. Maletzke, W. Hassan, D. dos Reis, and G. Batista. The importance of the test set size in quantification assessment. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI20, pages 2640–2646, 2020. <doi:10.24963/ijcai.2020/366>.

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NOTE 11 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Jun 9, 2026
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ERROR 9 OK · 2 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Apr 25, 2026
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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
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dependencies in R code

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Version History

4 tracked
new 0.2.0 Mar 10, 2026
updated 0.2.0 ← 0.1.5 diff Jan 19, 2022
updated 0.1.5 ← 0.1.4 diff Apr 12, 2021
new 0.1.4 Sep 22, 2020