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[Sap18a] From Conventional Data Analysis Methods to Big Data Analytics
Chapitres de Livre : Titre du livre: "Big Data for Insurance Companies", January 2018, Wiley, pp. 27-41, (doi: 10.1002/9781119489368.ch2) (isbn: 9781786300737)Mots clés: Big Data, Cross validation, Data analysis, regression, supervised classification
Résumé:
Data analysis in this chapter mainly means descriptive and exploratory methods, also known as unsupervised. The objective is to describe as well as structure a set of data that can be represented in the form of a rectangular table crossing n statistical units and p variables. Data analysis methods are essentially dimension reduction methods that are divided into two categories: factor methods; and the unsupervised classification methods or clustering. Data mining is a step in the knowledge discovery process, which involves applying data analysis algorithms. Data mining seeks to find predictive models of a Y denoted response, but from a very different perspective than that of conventional modeling. This chapter distinguishes regression methods where Y is quantitative, supervised classification methods (also called discrimination methods) where Y is categorical, most often with two modalities. The chapter also discusses new tools for big data processing, based on validation with data set aside.
BibTeX
| @inbook { | |||
| Sap18a, | |||
| title | = | "{Big Data for Insurance Companies}", | |
| chapter | = | "{From Conventional Data Analysis Methods to Big Data Analytics}", | |
| author | = | "G. Saporta", | |
| year | = | 2018, | |
| publisher | = | "Wiley", | |
| pages | = | "27-41", | |
| doi | = | "10.1002/9781119489368.ch2", | |
| isbn | = | " 9781786300737", | |
| } | |||
