'Good classification' diaporamas de présentation

Multivariate Data Analysis with T MVA

Multivariate Data Analysis with T MVA. Peter Speckmayer ( * ) (CERN) LCD Seminar, CERN, April 14, 2010. ( * ) On behalf of the present core developer team: A. Hoecker , P. Speckmayer, J. Stelzer , J. Therhaag , E. v. Toerne , H . Voss

1.11k views • 91 slides

New Tools for Evaluating the Results of Cluster Analyses Hilde Schaeper

Fourth German Stata Users Group Meeting. New Tools for Evaluating the Results of Cluster Analyses Hilde Schaeper Higher Education Information System (HIS), Hannover/Germany schaeper@his.de. Mannheim, March 31st, 2006. Main features of cluster analysis.

388 views • 29 slides

Fuzzy inference system and learning 08 july 2014

472 views • 23 slides

Geometry of Online Packing Linear Programs

Geometry of Online Packing Linear Programs. Marco Molinaro and R. Ravi Carnegie Mellon University. Packing Integer Programs (PIPs). n. Non-negative c , A , b Max st A has entries in [0,1]. A. x. b. m. ?. Online Packing Integer Programs.

284 views • 19 slides

Decision Trees

Decision Trees. Prof. A.L. Yuille. Stat 231. Fall 2004. Duda, Hart & Stork. Chp 81-8.3 . Decision Trees. Decision Trees. Binary Classification Trees. Data can be non-metric, list of binary attributes. 2. Classification Decision Trees. Nonmetric. Data is list of binary attributes.

787 views • 15 slides