Hostility measure for multi-level study of data complexity
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2023
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oai:localhost:PNK-73922023-03-31T07:44:37Z Hostility measure for multi-level study of data complexity Carmen, Lancho Isaac Martín De Diego, Diego Marina, Cuesta measure offering a multi-level complexity of supervised data CC BY omplexity measures aim to characterize the underlying complexity of supervised data. These measures tackle factors hindering the performance of Machine Learning (ML) classifiers like overlap, density, linearity, etc. The state-of-the-art has mainly focused on the dataset perspective of complexity, i.e., offering an estimation of the complexity of the whole dataset. Recently, the instance perspective has also been addressed. In this paper, the hostility measure, a complexity measure offering a multi-level (instance, class, and dataset) perspective of data complexity is proposed. 2023-03-31T07:44:37Z 2023-03-31T07:44:37Z 2023 Book https://link.springer.com/article/10.1007/s10489-022-03793-w https://dlib.phenikaa-uni.edu.vn/handle/PNK/7392 en application/pdf Springer |
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measure offering a multi-level complexity of supervised data |
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measure offering a multi-level complexity of supervised data Carmen, Lancho Isaac Martín De Diego, Diego Marina, Cuesta Hostility measure for multi-level study of data complexity |
description |
CC BY |
format |
Book |
author |
Carmen, Lancho Isaac Martín De Diego, Diego Marina, Cuesta |
author_facet |
Carmen, Lancho Isaac Martín De Diego, Diego Marina, Cuesta |
author_sort |
Carmen, Lancho |
title |
Hostility measure for multi-level study of data complexity |
title_short |
Hostility measure for multi-level study of data complexity |
title_full |
Hostility measure for multi-level study of data complexity |
title_fullStr |
Hostility measure for multi-level study of data complexity |
title_full_unstemmed |
Hostility measure for multi-level study of data complexity |
title_sort |
hostility measure for multi-level study of data complexity |
publisher |
Springer |
publishDate |
2023 |
url |
https://link.springer.com/article/10.1007/s10489-022-03793-w https://dlib.phenikaa-uni.edu.vn/handle/PNK/7392 |
_version_ |
1761912527078293504 |
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8.891145 |