PLearn 0.1
Namespaces | Functions
Ker_VMat_utils.cc File Reference
#include "Ker_VMat_utils.h"
#include <plearn/ker/Kernel.h>
#include <plearn/vmat/VMat.h>
#include <plearn/math/TVec.h>
#include <plearn/math/TopNI.h>
#include <plearn/math/BottomNI.h>
Include dependency graph for Ker_VMat_utils.cc:

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.

Detailed Description

Definition in file Ker_VMat_utils.cc.

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