May 30, 2014 · In this paper, we revise the definition of some measures that we presented in a previous work, that were designed for meta-learning based ...
In this paper, we revise the definition of some measures that we presented in a previous work, that were designed for meta-learning based instance selection.
In this work, the system updates the specification of a few measures that were created for instance selection based on meta-learning. Moreover, the system ...
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Apr 25, 2024 · A Set of Complexity Measures Designed for Applying Meta-Learning to Instance Selection. IEEE Trans. Knowl. Data Eng. 27(2): 354-367 (2015) ...
Oct 2, 2023 · In this work, we aim to investigate this by assessing the performance of Complexity Measures (global/data-level measures) & Instance Hardness Measures (local/ ...
In this paper, we revise the definition of some measures that we presented in a previous work, that were designed for meta-learning based instance selection.
A Set of Complexity Measures Designed for Applying Meta-Learning to Instance Selection. E Leyva, A González, R Pérez. IEEE, 0. 98 · Combining instance selection ...
Oct 22, 2024 · The goal of instance selection is to identify which instances (examples, patterns) in a large dataset should be selected as representatives ...
A set of complexity measures designed for applying meta-learning to instance selection. Leyva, E. González, A. Pérez, R. Revista: IEEE Transactions on ...
[PDF] Data complexity meta-features for regression problems
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This paper presents and analyses measures devoted to estimate the complexity of the function that should fitted to the data in regression problems, ...