Log of /trunk/tmva/src/PDEFoamKernelBase.cxx
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Modified
Wed Dec 22 09:03:52 2010 UTC (4 years, 1 month ago) by
avoigt
Original Path:
branches/dev/tmva/src/PDEFoamKernelBase.cxx
File length: 3053 byte(s)
Copied from:
branches/dev/tmvaValidation/PDEFoam3/src/PDEFoamKernelBase.cxx revision 37682
Diff to
previous 37678
Merge complete branch dev/tmvaValidation/PDEFoam3 into dev/tmva
Release notes:
==============
New PDEFoam structure:
----------------------
The different PDEFoam variants are now subclasses of the class
TMVA::PDEFoam. These variants are:
- PDEFoamEvent (stores the number of events)
- PDEFoamDiscriminant (stores the discriminant)
- PDEFoamTarget (stores a single target)
- PDEFoamMultiTarget (variation of PDEFoamEvent)
- PDEFoamDecisionTree (decision tree-like cell splitting)
Per default PDEFoam stores in the cells the number of events (event
weights) and therefore acts as an event density estimator. However,
the above listed derived classes override this behaviour to implement
certain PDEFoam variations.
The different PDEFoam's density estimators are now derived classes of
the abstract interface class TMVA::PDEFoamDensityBase. These density
estimators are:
- PDEFoamEventDensity (estimates the event density)
- PDEFoamDiscriminantDensity (estimates the discriminant density)
- PDEFoamTargetDensity (estimates the target density)
- PDEFoamDecisionTreeDensity (estimates decision tree separation type)
The various PDEFoam kernels are now separate from the PDEFoam class.
The abstract kernel interface is provided by the class
TMVA::PDEFoamKernelBase. The concrete classes PDEFoamKernelTrivial,
PDEFoamKernelLinN and PDEFoamKernelGauss implement specific kernel
estimators.
Extended PDEFoam functionality:
-------------------------------
* Multiclass classification via training of one discriminator foam
for each variable.
* The cell tree can now be plotted from the macro test/PlotFoams.C
This makes it easyer to compare the PDEFoam structure to a
decision tree etc.
* Variable importance ranking by counting the number of cuts made in
the diverse dimensions. The variable, for which the most cuts
were done is ranked highest.
Fixed bugs:
-----------
* The size of the sampling box in each dimension was 2*VolFrac times
the foam size in this dimension. This was contrast to the
intention and the documentation in the UserGuide. This is now
corrected: The size of the sampling box in each dimension is now
VolFrac times the foam size in this dimension. This implies that
the VolFrac default value must be changed from 0.0333 to 0.0666 to
lead the same results.
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