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finished for one sample

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Finished with several samples support, need regression testing

Gave a more relevant name to function (getVotes)

Finished implicit implementation

Removed printf, finished regresion testing

Fixed conversion warning

Finished test for Rtrees

Fixed documentation

Initialized variable

Added doxygen documentation

Added parameter name
This commit is contained in:
mrquorr
2017-01-31 23:31:10 -06:00
parent ec47a0a6de
commit d8425d8881
3 changed files with 123 additions and 0 deletions
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modules/ml/include/opencv2/ml.hpp
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@@ -1164,6 +1164,17 @@ public:
*/
CV_WRAP virtual Mat getVarImportance() const = 0;
/** Returns the result of each individual tree in the forest.
In case the model is a regression problem, the method will return each of the trees'
results for each of the sample cases. If the model is a classifier, it will return
a Mat with samples + 1 rows, where the first row gives the class number and the
following rows return the votes each class had for each sample.
@param samples Array containg the samples for which votes will be calculated.
@param results Array where the result of the calculation will be written.
@param flags Flags for defining the type of RTrees.
*/
CV_WRAP void getVotes(InputArray samples, OutputArray results, int flags) const;
/** Creates the empty model.
Use StatModel::train to train the model, StatModel::train to create and train the model,
Algorithm::load to load the pre-trained model.