mlquantify
Algorithms for Class Distribution Estimation
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.0 |
rolling linux/jammy R-4.5 | mlquantify_0.2.0.tar.gz |
168.9 KiB |
0.2.0 |
rolling linux/noble R-4.5 | mlquantify_0.2.0.tar.gz |
169.1 KiB |
0.2.0 |
rolling source/ R- | mlquantify_0.2.0.tar.gz |
105.7 KiB |
0.2.0 |
latest linux/jammy R-4.5 | mlquantify_0.2.0.tar.gz |
168.9 KiB |
0.2.0 |
latest linux/noble R-4.5 | mlquantify_0.2.0.tar.gz |
169.1 KiB |
0.2.0 |
latest source/ R- | mlquantify_0.2.0.tar.gz |
105.7 KiB |
0.2.0 |
2026-04-26 source/ R- | mlquantify_0.2.0.tar.gz |
105.7 KiB |
0.2.0 |
2026-04-23 source/ R- | mlquantify_0.2.0.tar.gz |
105.7 KiB |
0.2.0 |
2026-04-09 windows/windows R-4.5 | mlquantify_0.2.0.zip |
172.8 KiB |
0.2.0 |
2025-04-20 source/ R- | mlquantify_0.2.0.tar.gz |
105.7 KiB |