TMVA

• New reference page for configuration options
  The page is automatically generated for each new release. Next to the classifiers also exist information links for hints to improve the classifier performance (click on the "i" button). Many thanks to Zhiyi Liu (Fraser U) for suggesting this.
• Methods:
  • BDT: New Decision Tree Pruning algorithm: Cost Complexity Pruning a la CART. Written by Doug Schouten (Fraser U.). It replaces the old CostComplexity and CostComplexity2 algorithms.
  • BDT: New no splitting option (choosable with NCuts<0) that finds best split point by first sorting the events for each variable and then looping through all events, placing the cuts always in the middle between two of the sorted events, and finding the true possible maximum separation gain in the training sample by cutting on this variable.
  • BDT, AdaBoost The beta parameter is now an option (default is 1).
  • BDT: The node purity at which a node is classified as signal (respective background node) for determining the error fraction in the pruning became a parameter that can be set via the option NodePurityLimit (default is 0.5).
Dataset preparation:
• First implementation of a new preprocessing method: transformation of the variables first into a Gaussian distribution, then performing a decorrelation of the "Gaussianised" variables. The transformation is again done by default such that (by default) the signal distributions become Gaussian and are decorrelated. Note that simultaneous Gaussianisation and decorrelation of signal and background is only possible (and done) for methods, such as Likelihood, which test both hypotheses.
Bug fixes:
• Fix in Expected error pruning: Rather than multiplying both sides, the error on the node and the sub-tree, with the prune strength, now only the expected error of the sub-tree is scaled.
• Fix in FDA parsing of the input formula. There were problems when treating more than 10 parameters (thanks to Hugh Skottowe for reporting this).
• Calculation of "Separation": fixed bin-shift and normalisation bugs. Thanks to Dag Gillberg (Fraser U) for spotting these.
• Fixed problem in "SetSignal(Background)WeightExpression": signal (background weight expressions not existing in the background (signal) tree led to an abort of the tree reading ("Bad numerical expression"). Thanks to Alfio Rizzo (Brussels) for pointing this out.
• Fixed problem when specifying train and test tree explicitly. Some code was forgotten in the background part, creating incompatibilities. Thanks to Zhiyi Liu (Fraser U) for reporting this.