| /frameworks/ml/bordeaux/learning/stochastic_linear_ranker/native/ |
| common_defs.h | 32 enum KernelType { LINEAR, POLY, RBF };
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| stochastic_linear_ranker.h | 98 // RBF kernel, it implies the sigma parameter. In case of linear kernel,
141 // RBF kernel, it implies the sigma parameter. In case of linear kernel,
186 case RBF:
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| /external/opencv3/modules/java/src/ |
| ml+SVM.java | 26 RBF = 2,
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| /frameworks/ml/bordeaux/learning/stochastic_linear_ranker/jni/ |
| jni_stochastic_linear_ranker.cpp | 177 classifier->SetKernelType(learning_stochastic_linear::RBF);
332 case learning_stochastic_linear::RBF :
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| /external/opencv3/modules/ml/include/opencv2/ |
| ml.hpp | 498 For SVM::POLY, SVM::RBF, SVM::SIGMOID or SVM::CHI2. Default value is 1. */
559 See SVM::KernelTypes. Default value is SVM::RBF. */
596 different kernels (SVM::CHI2, SVM::INTER, SVM::RBF). The color depicts the class with max score.
609 /** Radial basis function (RBF), a good choice in most cases.
611 RBF=2,
614 /** Exponential Chi2 kernel, similar to the RBF kernel:
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| /external/opencv/ml/src/ |
| mlsvm.cpp | 170 svm_type(CvSVM::C_SVC), kernel_type(CvSVM::RBF), degree(0),
222 calc_func = params->kernel_type == CvSVM::RBF ? &CvSVMKernel::calc_rbf :
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| /external/opencv3/modules/ml/src/ |
| svm.cpp | 122 kernelType = SVM::RBF;
310 case SVM::RBF:
[all...] |
| /external/opencv3/modules/ml/test/ |
| test_mltests2.cpp | 68 if( !str.compare("RBF") )
69 return SVM::RBF;
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| /external/opencv/ml/include/ |
| ml.h | 330 double gamma; // for poly/rbf/sigmoid
489 enum { LINEAR=0, POLY=1, RBF=2, SIGMOID=3 };
[all...] |
| /external/opencv3/apps/traincascade/ |
| old_ml.hpp | 302 CV_PROP_RW double gamma; // for poly/rbf/sigmoid/chi2
464 enum { LINEAR=0, POLY=1, RBF=2, SIGMOID=3, CHI2=4, INTER=5 };
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| /cts/apps/CtsVerifier/libs/ |
| opencv3-android.jar | |
