Skip to Main content Skip to Navigation
Conference papers

Models for Understanding versus Models for Prediction

Gilbert Saporta 1
1 CEDRIC - MSDMA - CEDRIC. Méthodes statistiques de data-mining et apprentissage
CEDRIC - Centre d'études et de recherche en informatique et communications
Abstract : According to a standard point of view, statistical modelling consists in establishing a parsimonious representation of a random phenomenon, generally based upon the knowledge of an expert of the application field: the aim of a model is to provide a better understanding of data and of the underlying mechanism which have produced it. On the other hand, Data Mining and KDD deal with predictive modelling: models are merely algorithms and the quality of a model is assessed by its performance for predicting new observations. In this communication, we develop some general considerations about both aspects of modelling.
Document type :
Conference papers
Complete list of metadata

Cited literature [10 references]  Display  Hide  Download
Contributor : Laboratoire Cedric <>
Submitted on : Tuesday, March 24, 2020 - 5:41:02 PM
Last modification on : Wednesday, March 25, 2020 - 3:44:02 PM


Files produced by the author(s)




Gilbert Saporta. Models for Understanding versus Models for Prediction. Compstat 2008, Aug 2008, Porto, Portugal. pp.315-322, ⟨10.1007/978-3-7908-2084-3_26⟩. ⟨hal-01125563⟩



Record views


Files downloads