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XXX Dataset might need to get labelweights parameter which could be
used by some classifiers
Mapper Dataset (S1)
| \- appendtohistory(item)
| \-ICAMapper \ |
MaskMapper \------- MappedDataset (S1, Mapper)
\ forward(ndarray) |
MaskedDataset (S1, mask)
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NiftiDataset
Splitter ErrorFunction
| |
NFoldSplitter(S2) CrossValidation
\ call(dataset)
Clf (LinearSVM)
train \- weights
predict
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BoostedClassifier
Clf <- optimizeClassifier(optimizer, clf, parameter_to_optimize)
default combiner = average
OptimizerAlgorithm
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LineSearchOptimizer GridSearch FeatureStrip(SensitivityAnalyzer)
after train return ErrorFunction, sensitivity,
Optimizer
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ParameterOptimizer(optimizeralgorithm, parameter, classifier)
BoostedOptimizer(splitter, optimizer)
# NOTES
Sensitivity -> RankList (N.argsort)
sens <- Combine
dataset <- selectImportantFeature
RFE(dataset, sensAnalyzer):
do
sens <- sensAnalyzer(dataset)
dataset <- selectImportantFeature(dataset, sens)
until the world collapses into
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