Tajmouati, S. and Abarda, A. and Moudden, M.E. and Dakkon, M. and Esghir, M. (2018) A study of the application of statistical methods for big data. In: UNSPECIFIED.

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Abstract

The use of analysis and classification methods for big data is difficult. Several proposals consist in dividing randomly the population into b sub-samples and aggregating the parameters using an estimator based on the average parameters of these selected sub-samples. This paper aims to find a solution that minimizes calculations by selecting a small number b∗ sub-samples and keeping the same precision. We can apply this approach to the several method to measure its relevance. © 2018 Association for Computing Machinery.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Uncontrolled Keywords: Learning algorithms; Optimization, Classification methods; Latent class analysis; Massive data; Sub-samples, Big data
Subjects: Computer Science
Divisions: SCIENTIFIC PRODUCTION > Computer Science
Depositing User: Administrateur Eprints Administrateur Eprints
Last Modified: 31 Jan 2020 15:46
URI: http://eprints.umi.ac.ma/id/eprint/2377

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