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problexity-An open-source Python library for supervised learning problem complexity assessment
DOI:10.1016/j.neucom.2022.11.056.png)
摘要
En 中文
The problem's complexity assessment is an essential element of many topics in the supervised learning domain. It plays a significant role in meta-learning - becoming the basis for determining meta-attributes or multi-criteria optimization - allowing the evaluation of the training set resampling without needing to rebuild the recognition model. The tools currently available for the academic community, which would enable the calculation of problem complexity measures, are available only as libraries of the C++ and R languages. This paper describes the software module that allows for the estimation of 22 classification complexity measures and 12 regression complexity measures for the Python language - compatible with the scikit-learn programming interface - allowing for the implementation of research using them in the most popular programming environment of the machine learning community. (c) 2022 Elsevier B.V. All rights reserved.
Keyword:
Problem complexity
Classification
Regression
Python
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
机构
引用论文
How Complex Is Your Classification Problem?: A Survey on Measuring Classification Complexity您的分类问题有多复杂?: 测量分类复杂性的调查
Effect of label noise in the complexity of classification problems标签噪声对分类问题复杂性的影响
NEUROCOMPUTING
IF6.5
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