generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Increasing the dimension of features space in the SVMSGD::train function.

Browse Source
This commit is contained in:
Marina Noskova
2016-02-03 15:31:05 +03:00
parent 40bf97c6d1
commit acd74037b3
8 changed files with 412 additions and 349 deletions
Download Patch File Download Diff File Expand all files Collapse all files

28
modules/ml/test/test_svmsgd.cpp
View File

@@ -52,7 +52,7 @@ using cv::ml::TrainData;
class CV_SVMSGDTrainTest : public cvtest::BaseTest
{
public:
CV_SVMSGDTrainTest(Mat _weights, float _shift);
CV_SVMSGDTrainTest(Mat _weights, float shift);
private:
virtual void run( int start_from );
float decisionFunction(Mat sample, Mat weights, float shift);
@@ -60,7 +60,7 @@ private:
cv::Ptr<TrainData> data;
cv::Mat testSamples;
cv::Mat testResponses;
static const int TEST_VALUE_LIMIT = 50;
static const int TEST_VALUE_LIMIT = 500;
};
CV_SVMSGDTrainTest::CV_SVMSGDTrainTest(Mat weights, float shift)
@@ -81,6 +81,11 @@ CV_SVMSGDTrainTest::CV_SVMSGDTrainTest(Mat weights, float shift)
responses.at<float>( sampleIndex ) = decisionFunction(samples.row(sampleIndex), weights, shift) > 0 ? 1 : -1;
}
std::cout << "real weights\n" << weights/norm(weights) << "\n" << std::endl;
std::cout << "real shift \n" << shift/norm(weights) << "\n" << std::endl;
data = TrainData::create( samples, cv::ml::ROW_SAMPLE, responses );
int testSamplesCount = 100000;
@@ -100,8 +105,9 @@ void CV_SVMSGDTrainTest::run( int /*start_from*/ )
cv::Ptr<SVMSGD> svmsgd = SVMSGD::create();
svmsgd->setOptimalParameters(SVMSGD::ASGD);
svmsgd->setTermCriteria(TermCriteria(TermCriteria::EPS, 0, 0.00005));
svmsgd->train( data );
svmsgd->train(data);
Mat responses;
@@ -116,6 +122,12 @@ void CV_SVMSGDTrainTest::run( int /*start_from*/ )
errCount++;
}
float normW = norm(svmsgd->getWeights());
std::cout << "found weights\n" << svmsgd->getWeights()/normW << "\n" << std::endl;
std::cout << "found shift \n" << svmsgd->getShift()/normW << "\n" << std::endl;
float err = (float)errCount / testSamplesCount;
std::cout << "err " << err << std::endl;
@@ -138,8 +150,8 @@ TEST(ML_SVMSGD, train0)
weights.create(1, varCount, CV_32FC1);
weights.at<float>(0) = 1;
weights.at<float>(1) = 0;
float shift = 5;
cv::RNG rng(1);
float shift = rng.uniform(-varCount, varCount);
CV_SVMSGDTrainTest test(weights, shift);
test.safe_run();
@@ -157,7 +169,7 @@ TEST(ML_SVMSGD, train1)
cv::RNG rng(0);
rng.fill(weights, RNG::UNIFORM, lowerLimit, upperLimit);
float shift = rng.uniform(-5.f, 5.f);
float shift = rng.uniform(-varCount, varCount);
CV_SVMSGDTrainTest test(weights, shift);
test.safe_run();
@@ -175,8 +187,8 @@ TEST(ML_SVMSGD, train2)
cv::RNG rng(0);
rng.fill(weights, RNG::UNIFORM, lowerLimit, upperLimit);
float shift = rng.uniform(-1000.f, 1000.f);
float shift = rng.uniform(-varCount, varCount);
CV_SVMSGDTrainTest test(weights, shift);
CV_SVMSGDTrainTest test(weights,shift);
test.safe_run();
}