PLearn 0.1
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#include <plearn/base/Object.h>
#include "VMat_basic_stats.h"
#include "MemoryVMatrix.h"
#include "ShiftAndRescaleVMatrix.h"
#include <plearn/math/stats_utils.h>
#include <plearn/math/VecStatsCollector.h>
#include <plearn/math/TMat_maths.h>
Go to the source code of this file.
Namespaces | |
namespace | PLearn |
< for swap | |
Functions | |
void | PLearn::computeWeightedMean (const Vec &weights, const VMat &d, Vec &meanvec) |
void | PLearn::computeRange (const VMat &d, Vec &minvec, Vec &maxvec) |
void | PLearn::computeRowMean (const VMat &d, Vec &meanvec) |
Compute mean of each row (the returned vector has length d->length()). | |
void | PLearn::computeMean (const VMat &d, Vec &meanvec) |
Compute basic statistics over all samples. | |
Mat | PLearn::computeBasicStats (const VMat &m) |
TVec< Mat > | PLearn::computeConditionalMeans (const VMat &trainset, int targetsize, Mat &basic_stats) |
void | PLearn::computeMeanAndVariance (const VMat &d, Vec &meanvec, Vec &variancevec, real epsilon) |
void | PLearn::computeInputMean (const VMat &d, Vec &meanvec) |
void | PLearn::computeInputMeanAndCovar (const VMat &d, Vec &meanvec, Mat &covarmat, real epsilon) |
void | PLearn::computeInputMeanAndVariance (const VMat &d, Vec &meanvec, Vec &var, real epsilon) |
void | PLearn::computeInputMeanAndStddev (const VMat &d, Vec &meanvec, Vec &stddev, real epsilon) |
void | PLearn::computeWeightedMeanAndCovar (const Vec &weights, const VMat &d, Vec &meanvec, Mat &covarmat, real epsilon) |
void | PLearn::computeMeanAndCovar (const VMat &d, Vec &meanvec, Mat &covarmat, real epsilon) |
void | PLearn::computeCovar (const VMat &d, const Vec &mu, Mat &covarmat, real epsilon=0.0) |
Computes covariance matrix given mean mu. | |
void | PLearn::computeInputCovar (const VMat &d, const Vec &mu, Mat &covarmat, real epsilon=0.0) |
Computes covariance matrix given mean mu. | |
void | PLearn::computeMeanAndStddev (const VMat &d, Vec &meanvec, Vec &stddevvec, real epsilon) |
void | PLearn::autocorrelation_function (const VMat &data, Mat &acf) |
VMat | PLearn::normalize (const VMat &d, const Vec &meanvec, const Vec &stddevvec) |
VMat | PLearn::normalize (const VMat &d, int inputsize, int ntrain) |
Here, mean and stddev are estimated on d.subMat(0,0,ntrain,inputsize). | |
VMat | PLearn::normalize (VMat d, int inputsize) |
void | PLearn::correlations (const VMat &x, const VMat &y, Mat &r, Mat &pvalues, bool ignore_missing=false) |
Compute the correlations between each of the columns of x and each of the columns of y. |
Definition in file VMat_basic_stats.cc.