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changed GBT parameters in sample

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This commit is contained in:
Maria Dimashova 2011-05-04 14:49:02 +00:00
parent 8bbbd93410
commit 1b5f5dd371
1 changed files with 6 additions and 9 deletions
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15
samples/cpp/points_classifier.cpp
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@ -272,6 +272,7 @@ void find_decision_boundary_GBT()
Mat trainSamples, trainClasses; Mat trainSamples, trainClasses;
prepare_train_data( trainSamples, trainClasses ); prepare_train_data( trainSamples, trainClasses );
trainClasses.convertTo( trainClasses, CV_32FC1 );
// learn classifier // learn classifier
CvGBTrees gbtrees; CvGBTrees gbtrees;
@ -279,13 +280,13 @@ void find_decision_boundary_GBT()
Mat var_types( 1, trainSamples.cols + 1, CV_8UC1, Scalar(CV_VAR_ORDERED) ); Mat var_types( 1, trainSamples.cols + 1, CV_8UC1, Scalar(CV_VAR_ORDERED) );
var_types.at<uchar>( trainSamples.cols ) = CV_VAR_CATEGORICAL; var_types.at<uchar>( trainSamples.cols ) = CV_VAR_CATEGORICAL;
CvGBTreesParams params( CvGBTrees::SQUARED_LOSS, // loss_function_type CvGBTreesParams params( CvGBTrees::DEVIANCE_LOSS, // loss_function_type
100, // weak_count 100, // weak_count
0.05f, // shrinkage 0.1f, // shrinkage
0.6f, // subsample_portion 1.0f, // subsample_portion
2, // max_depth 2, // max_depth
false // use_surrogates ) false // use_surrogates )
); );
gbtrees.train( trainSamples, CV_ROW_SAMPLE, trainClasses, Mat(), Mat(), var_types, Mat(), params ); gbtrees.train( trainSamples, CV_ROW_SAMPLE, trainClasses, Mat(), Mat(), var_types, Mat(), params );
@ -315,10 +316,6 @@ void find_decision_boundary_RF()
// learn classifier // learn classifier
CvRTrees rtrees; CvRTrees rtrees;
Mat var_types( 1, trainSamples.cols + 1, CV_8UC1, Scalar(CV_VAR_ORDERED) );
var_types.at<uchar>( trainSamples.cols ) = CV_VAR_CATEGORICAL;
CvRTParams params( 4, // max_depth, CvRTParams params( 4, // max_depth,
2, // min_sample_count, 2, // min_sample_count,
0.f, // regression_accuracy, 0.f, // regression_accuracy,
@ -332,7 +329,7 @@ void find_decision_boundary_RF()
CV_TERMCRIT_ITER // termcrit_type CV_TERMCRIT_ITER // termcrit_type
); );
rtrees.train( trainSamples, CV_ROW_SAMPLE, trainClasses, Mat(), Mat(), var_types, Mat(), params ); rtrees.train( trainSamples, CV_ROW_SAMPLE, trainClasses, Mat(), Mat(), Mat(), Mat(), params );
Mat testSample(1, 2, CV_32FC1 ); Mat testSample(1, 2, CV_32FC1 );
for( int y = 0; y < img.rows; y += testStep ) for( int y = 0; y < img.rows; y += testStep )