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|   | Machine Learning |  | 
| Namespaces | |
| vigra::rf3 | |
| Random forest version 3. | |
| vigra::rf::visitors | |
| Visitors to extract information during training of vigra::RandomForest version 2. | |
| Classes | |
| class | DepthStop | 
| Random forest 'maximum depth' stop criterion.  More... | |
| class | EntropyScore | 
| Functor that computes the entropy score.  More... | |
| class | GiniScore | 
| Functor that computes the gini score.  More... | |
| class | KolmogorovSmirnovScore | 
| Functor that computes the Kolmogorov-Smirnov score.  More... | |
| class | NodeComplexityStop | 
| Random forest 'node complexity' stop criterion.  More... | |
| class | NumInstancesStop | 
| Random forest 'number of datapoints' stop criterion.  More... | |
| class | ProblemSpec< LabelType > | 
| problem specification class for the random forest.  More... | |
| class | PurityStop | 
| Random forest 'node purity' stop criterion.  More... | |
| class | RandomForest< LabelType, PreprocessorTag > | 
| Random forest version 2 (see also vigra::rf3::RandomForest for version 3)  More... | |
| class | RandomForestOptions | 
| Options object for the random forest.  More... | |
| class | Sampler< Random > | 
| Create random samples from a sequence of indices.  More... | |
| class | SamplerOptions | 
| Options object for the Sampler class.  More... | |
This module provides classification algorithms that map features to labels or label probabilities. Look at the vigra::RandomForest class (for implementation version 2) or the vigra::rf3::random_forest() factory function (for implementation version 3) for an overview of the functionality as well as use cases.
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© Ullrich Köthe     (ullrich.koethe@iwr.uni-heidelberg.de)  | 
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