9 / 43 A. Hoecker: Data Mining with TMVAFreiburg Seminar, May 9, 2007 What is TMVA The various classifiers have very different properties Ideally, all
{"Image DocumentName": "A. Hoecker: Data Mining with TMVA", "Image ImageDescription": "What is TMVA. The various classifiers have very different properties. Ideally, all should be tested for a given problem. Systematically choose the best performing and simplest classifier. Comparisons between classifiers improves the understanding and takes away mysticism. TMVA \u2015 Toolkit for multivariate data analysis. Framework for parallel training, testing, evaluation and application of MV classifiers. Training events can have weights. A large number of linear, nonlinear, likelihood and rule-based classifiers implemented. Each classifier provides a ranking of the input variables. The input variables can be decorrelated or projected upon their principal components. Training results and full configuration are written to weight files and applied by a Reader. Clear and simple user interface. Freiburg Seminar, May 9, A. Hoecker: Data Mining with TMVA.", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}