mlquantify
0.2.0Algorithms for Class Distribution Estimation
Overview
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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Health
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- NOTE2026-06-0911 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0810 OK · 2 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-05-0211 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-259 OK · 2 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-03-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 89%
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Checks run against github.com/andregustavom/mlquantify on 2026-07-19.
Dependencies
Nothing depends on this yet.
Code & Tests
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People & History
3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- 0.2.0Latest
- RR 4.1.0 released · 2021-05-18
- 0.1.52021-04-13 · diff ↗
- unarchivedReturned to CRAN2021-04-13
- archivedRemoved from CRAN2021-04-06check problems were not corrected in time
- 0.1.42020-09-23
- RR 4.0.0 released · 2020-04-24
Package metadata
- First published
- 2020-09-23
- Total releases
- 3 / 6 yrs
- License
- GPL (>= 2.0)
- Bundled data
- 83 KB / 1 file
- Download size
- 105 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet