Searched refs:nallvars (Results 1 - 3 of 3) sorted by relevance

/external/opencv3/modules/ml/src/
H A Dnbayes.cpp52 nallvars = 0;
72 nallvars = __nallvars;
98 if( nallvars != __nallvars ||
312 if( samples.type() != CV_32F || samples.cols != nallvars )
314 "The input samples must be 32f matrix with the number of columns = nallvars" );
345 fs << "var_count" << (var_idx.empty() ? nallvars : (int)var_idx.total());
346 fs << "var_all" << nallvars; local
385 fn["var_all"] >> nallvars; local
387 if( nallvars <= 0 )
440 nallvars
448 int nallvars; member in class:cv::ml::NormalBayesClassifierImpl
[all...]
H A Drtrees.cpp143 int nallvars = w->data->getNAllVars(); local
145 vector<float> samplebuf(nallvars);
149 Mat sample0, sample(nallvars, 1, CV_32F, &samplebuf[0]);
168 varImportance.resize(nallvars, 0.f);
204 sample = Mat( nallvars, 1, CV_32F, psamples + sstep0*w->sidx[j], sstep1*sizeof(psamples[0]) );
254 sample0 = Mat( nallvars, 1, CV_32F, psamples + sstep0*w->sidx[j], sstep1*sizeof(psamples[0]) );
255 for( k = 0; k < nallvars; k++ )
278 for( vi_ = 0; vi_ < nallvars; vi_++ )
H A Dtree.cpp149 int nallvars = data->getNAllVars(); local
155 setRangeVector(varIdx, nallvars);
207 int nallvars = (int)varType.size(); local
208 compVarIdx.assign(nallvars, -1);
213 CV_Assert( 0 <= vi && vi < nallvars && vi > prevIdx );

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