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On Data-Preparation Efficiency Application on Breast Cancer Classification

Abstract : Quantifying the informative state of a dataset for a classification task is an important question. In this paper, we try to circumscribe this notion by introducing some new measures and enunciating some principles about data preparation. We experiment the interest of these measures and the validity of these principles by introducing several protocols designed for comparing different ways to prepare the data. We conclude by relating the efficiency of the data preparation and its theoretical diversity.
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Preprints, Working Papers, ...
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Contributor : Mouna Sabrine Mayouf <>
Submitted on : Wednesday, June 2, 2021 - 11:02:08 AM
Last modification on : Wednesday, June 9, 2021 - 10:00:24 AM


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  • HAL Id : hal-03246076, version 1


Mouna Sabrine Mayouf, Florence Dupin de Saint Cyr - Bannay. On Data-Preparation Efficiency Application on Breast Cancer Classification. 2021. ⟨hal-03246076⟩



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