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Merge pull request #8116 from mrquorr:master
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@@ -1206,6 +1206,17 @@ public:
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*/
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CV_WRAP virtual Mat getVarImportance() const = 0;
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/** Returns the result of each individual tree in the forest.
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In case the model is a regression problem, the method will return each of the trees'
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results for each of the sample cases. If the model is a classifier, it will return
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a Mat with samples + 1 rows, where the first row gives the class number and the
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following rows return the votes each class had for each sample.
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@param samples Array containg the samples for which votes will be calculated.
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@param results Array where the result of the calculation will be written.
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@param flags Flags for defining the type of RTrees.
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*/
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CV_WRAP void getVotes(InputArray samples, OutputArray results, int flags) const;
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/** Creates the empty model.
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Use StatModel::train to train the model, StatModel::train to create and train the model,
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Algorithm::load to load the pre-trained model.
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