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virtual int | getBoostType () const =0 |
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virtual int | getWeakCount () const =0 |
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virtual double | getWeightTrimRate () const =0 |
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virtual void | setBoostType (int val)=0 |
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virtual void | setWeakCount (int val)=0 |
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virtual void | setWeightTrimRate (double val)=0 |
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virtual int | getCVFolds () const =0 |
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virtual int | getMaxCategories () const =0 |
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virtual int | getMaxDepth () const =0 |
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virtual int | getMinSampleCount () const =0 |
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virtual const std::vector< Node > & | getNodes () const =0 |
| Returns all the nodes. More...
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virtual cv::Mat | getPriors () const =0 |
| The array of a priori class probabilities, sorted by the class label value. More...
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virtual float | getRegressionAccuracy () const =0 |
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virtual const std::vector< int > & | getRoots () const =0 |
| Returns indices of root nodes. More...
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virtual const std::vector< Split > & | getSplits () const =0 |
| Returns all the splits. More...
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virtual const std::vector< int > & | getSubsets () const =0 |
| Returns all the bitsets for categorical splits. More...
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virtual bool | getTruncatePrunedTree () const =0 |
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virtual bool | getUse1SERule () const =0 |
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virtual bool | getUseSurrogates () const =0 |
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virtual void | setCVFolds (int val)=0 |
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virtual void | setMaxCategories (int val)=0 |
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virtual void | setMaxDepth (int val)=0 |
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virtual void | setMinSampleCount (int val)=0 |
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virtual void | setPriors (const cv::Mat &val)=0 |
| The array of a priori class probabilities, sorted by the class label value. More...
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virtual void | setRegressionAccuracy (float val)=0 |
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virtual void | setTruncatePrunedTree (bool val)=0 |
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virtual void | setUse1SERule (bool val)=0 |
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virtual void | setUseSurrogates (bool val)=0 |
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virtual float | calcError (const Ptr< TrainData > &data, bool test, OutputArray resp) const |
| Computes error on the training or test dataset. More...
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virtual bool | empty () const CV_OVERRIDE |
| Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...
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virtual int | getVarCount () const =0 |
| Returns the number of variables in training samples. More...
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virtual bool | isClassifier () const =0 |
| Returns true if the model is classifier. More...
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virtual bool | isTrained () const =0 |
| Returns true if the model is trained. More...
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virtual float | predict (InputArray samples, OutputArray results=noArray(), int flags=0) const =0 |
| Predicts response(s) for the provided sample(s) More...
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virtual bool | train (const Ptr< TrainData > &trainData, int flags=0) |
| Trains the statistical model. More...
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virtual bool | train (InputArray samples, int layout, InputArray responses) |
| Trains the statistical model. More...
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| Algorithm () |
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virtual | ~Algorithm () |
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virtual void | clear () |
| Clears the algorithm state. More...
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virtual String | getDefaultName () const |
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virtual void | read (const FileNode &fn) |
| Reads algorithm parameters from a file storage. More...
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virtual void | save (const String &filename) const |
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virtual void | write (FileStorage &fs) const |
| Stores algorithm parameters in a file storage. More...
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void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
| simplified API for language bindings This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More...
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