/** * <p>Trains a boosted tree classifier.</p> * * <p>The train method follows the common template of "CvStatModel.train". The * responses must be categorical, which means that boosted trees cannot be built * for regression, and there should be two classes.</p> * * @param trainData a trainData * @param tflag a tflag * @param responses a responses * @param varIdx a varIdx * @param sampleIdx a sampleIdx * @param varType a varType * @param missingDataMask a missingDataMask * @param params a params * @param update Specifies whether the classifier needs to be updated * (<code>true</code>, the new weak tree classifiers added to the existing * ensemble) or the classifier needs to be rebuilt from scratch * (<code>false</code>). * * @see <a href="http://docs.opencv.org/modules/ml/doc/boosting.html#cvboost-train">org.opencv.ml.CvBoost.train</a> */ public boolean train(Mat trainData, int tflag, Mat responses, Mat varIdx, Mat sampleIdx, Mat varType, Mat missingDataMask, CvBoostParams params, boolean update) { boolean retVal = train_0(nativeObj, trainData.nativeObj, tflag, responses.nativeObj, varIdx.nativeObj, sampleIdx.nativeObj, varType.nativeObj, missingDataMask.nativeObj, params.nativeObj, update); return retVal; }
/** * <p>Trains a boosted tree classifier.</p> * * <p>The train method follows the common template of "CvStatModel.train". The * responses must be categorical, which means that boosted trees cannot be built * for regression, and there should be two classes.</p> * * @param trainData a trainData * @param tflag a tflag * @param responses a responses * @param varIdx a varIdx * @param sampleIdx a sampleIdx * @param varType a varType * @param missingDataMask a missingDataMask * @param params a params * @param update Specifies whether the classifier needs to be updated * (<code>true</code>, the new weak tree classifiers added to the existing * ensemble) or the classifier needs to be rebuilt from scratch * (<code>false</code>). * * @see <a href="http://docs.opencv.org/modules/ml/doc/boosting.html#cvboost-train">org.opencv.ml.CvBoost.train</a> */ public boolean train(Mat trainData, int tflag, Mat responses, Mat varIdx, Mat sampleIdx, Mat varType, Mat missingDataMask, CvBoostParams params, boolean update) { boolean retVal = train_0(nativeObj, trainData.nativeObj, tflag, responses.nativeObj, varIdx.nativeObj, sampleIdx.nativeObj, varType.nativeObj, missingDataMask.nativeObj, params.nativeObj, update); return retVal; }
/** * <p>Trains a boosted tree classifier.</p> * * <p>The train method follows the common template of "CvStatModel.train". The * responses must be categorical, which means that boosted trees cannot be built * for regression, and there should be two classes.</p> * * @param trainData a trainData * @param tflag a tflag * @param responses a responses * @param varIdx a varIdx * @param sampleIdx a sampleIdx * @param varType a varType * @param missingDataMask a missingDataMask * @param params a params * @param update Specifies whether the classifier needs to be updated * (<code>true</code>, the new weak tree classifiers added to the existing * ensemble) or the classifier needs to be rebuilt from scratch * (<code>false</code>). * * @see <a href="http://docs.opencv.org/modules/ml/doc/boosting.html#cvboost-train">org.opencv.ml.CvBoost.train</a> */ public boolean train(Mat trainData, int tflag, Mat responses, Mat varIdx, Mat sampleIdx, Mat varType, Mat missingDataMask, CvBoostParams params, boolean update) { boolean retVal = train_0(nativeObj, trainData.nativeObj, tflag, responses.nativeObj, varIdx.nativeObj, sampleIdx.nativeObj, varType.nativeObj, missingDataMask.nativeObj, params.nativeObj, update); return retVal; }
/** * <p>Trains a boosted tree classifier.</p> * * <p>The train method follows the common template of "CvStatModel.train". The * responses must be categorical, which means that boosted trees cannot be built * for regression, and there should be two classes.</p> * * @param trainData a trainData * @param tflag a tflag * @param responses a responses * @param varIdx a varIdx * @param sampleIdx a sampleIdx * @param varType a varType * @param missingDataMask a missingDataMask * @param params a params * @param update Specifies whether the classifier needs to be updated * (<code>true</code>, the new weak tree classifiers added to the existing * ensemble) or the classifier needs to be rebuilt from scratch * (<code>false</code>). * * @see <a href="http://docs.opencv.org/modules/ml/doc/boosting.html#cvboost-train">org.opencv.ml.CvBoost.train</a> */ public boolean train(Mat trainData, int tflag, Mat responses, Mat varIdx, Mat sampleIdx, Mat varType, Mat missingDataMask, CvBoostParams params, boolean update) { boolean retVal = train_0(nativeObj, trainData.nativeObj, tflag, responses.nativeObj, varIdx.nativeObj, sampleIdx.nativeObj, varType.nativeObj, missingDataMask.nativeObj, params.nativeObj, update); return retVal; }