PLearn 0.1
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#include <plearn/math/TVec.h>
Go to the source code of this file.
Namespaces | |
namespace | PLearn |
< for swap | |
Functions | |
void | PLearn::evaluateKernel (Ker ker, VMat vm, int v1_startcol, int v1_ncols, const Vec &v2, const Vec &result, int startrow, int nrows) |
real | PLearn::evaluateKernelSum (Ker ker, VMat vm, int v1_startcol, int v1_ncols, const Vec &v2, int startrow=0, int nrows=-1, int ignore_this_row=-1) |
returns sum_i [ ker( m(i).subVec(v1_startcol,v1_ncols) , v2) ] | |
real | PLearn::evaluateKernelWeightedTargetSum (Ker ker, VMat vm, int v1_startcol, int v1_ncols, const Vec &v2, int t_startcol, int t_ncols, Vec &targetsum, int startrow=0, int nrows=-1, int ignore_this_row=-1) |
targetsum := sum_i [ m(i).subVec(t_startcol,t_ncols) * ker( m(i).subVec(v1_startcol,v1_ncols) , v2) ] and returns sum_i [ ker( m(i).subVec(v1_startcol,v1_ncols) , v2) ] | |
TVec< pair< real, int > > | PLearn::evaluateKernelTopN (int N, Ker ker, VMat vm, int v1_startcol, int v1_ncols, const Vec &v2, int startrow, int nrows, int ignore_this_row) |
TVec< pair< real, int > > | PLearn::evaluateKernelBottomN (int N, Ker ker, VMat vm, int v1_startcol, int v1_ncols, const Vec &v2, int startrow=0, int nrows=-1, int ignore_this_row=-1) |
same as evaluateKernelTopN but will look for the N smallest values instead of top values. |
Definition in file Ker_VMat_utils.h.