PLearn 0.1
Namespaces | Functions
databases.h File Reference
#include "UCISpecification.h"
#include <plearn/vmat/VMat.h>
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Namespaces

namespace  PLearn
 

< for swap


Functions

Mat PLearn::input2dSet (const PPath &filename="data2d.amat")
 This will input a 2d binary classification problem (launches a java applet)
void PLearn::normalizeDataSets (Mat &training_set, Mat &test_set)
 normalize both training_set and test_set according to mean and stddev computed on training_set
void PLearn::normalizeDataSets (Mat &training_set, Mat &validation_set, Mat &test_set)
void PLearn::normalizeDataSets (VMat &training_set, VMat &validation_set, VMat &test_set)
void PLearn::splitTrainValidTest (VMat &data_set, VMat &train_set, VMat &valid_set, real valid_fraction, VMat &test_set, real test_fraction, bool normalize)
VMat PLearn::reduceInputSize (real fraction, VMat data)
VMat PLearn::reduceDataSetSize (real fraction, VMat data)
void PLearn::remapClassnums (VMat &data, real remap_minval_to, real remap_maxval_to)
 remaps classnums to {0,1} or to {-1,+1}
int PLearn::loadBreastCancer (VMat &training_set, VMat &validation_set, VMat &test_set, int ntrain, int nvalid, bool uniq=true)
 These calls return the number of classes...
int PLearn::loadDiabetes (VMat &training_set, VMat &validation_set, VMat &test_set, int ntrain, int nvalid)
int PLearn::loadATT800 (VMat &training_set, VMat &test_set)
int PLearn::loadLetters (VMat &training_set, VMat &validation_set, VMat &test_set, char *which_letters, real validation_fraction, real test_fraction, bool do_shuffle)
int PLearn::loadLetters (VMat &training_set, VMat &validation_set, VMat &test_set, int n_letters, real validation_fraction, real test_fraction, bool do_shuffle)
void PLearn::loadCorelDatamat (int classnum, Mat &train, Mat &valid, Mat &test)
Mat PLearn::smoothCorelHisto (Mat &data)
void PLearn::loadCorel (Mat &training_set, Mat &validation_set, Mat &test_set, int negative_class, int positive_class)
void PLearn::loadCallxx (int year, VMat &d)
VMat PLearn::loadBreastCancerWisconsin (bool normalize, bool uniq)
VMat PLearn::loadSonar ()
VMat PLearn::loadIonosphere ()
VMat PLearn::loadDiabetes (bool normalize)
VMat PLearn::loadPimaIndians (bool normalize)
VMat PLearn::loadLetters (const char *class0, const char *class1, bool normalize)
VMat PLearn::loadLetters (bool normalize)
VMat PLearn::loadLetters (int n_letters, bool do_shuffle)
void PLearn::loadUSPS (VMat &trainset, VMat &testset, bool use_smooth)
VMat PLearn::loadUSPS (bool use_smooth)
VMat PLearn::loadHousing (bool normalize)
void PLearn::loadUCI (VMat &trainset, VMat &testset, VMat &allset, string db_spec, string id, bool &normalize, const string &type)
 Load the train, test and all datasets for a UCI database.
void PLearn::loadUCISet (VMat &data, string file, PP< UCISpecification > uci_spec)
 Load a specific UCI dataset in the given VMatrix.
void PLearn::loadUCIAMat (VMat &data, string file, PP< UCISpecification > uci_spec)
 Load a AMAT format UCI dataset in the given VMatrix.
void PLearn::loadUCISet (VMat &data, PP< UCISpecification > uci_spec)
 Load a specific UCI dataset in the given VMatrix.
string PLearn::loadClassificationDatasetHelp ()
string PLearn::loadUCIDatasetsHelp ()
void PLearn::loadClassificationDataset (const string &datasetname, int &inputsize, int &nclasses, VMat &trainset, VMat &testset, bool normalizeinputs, VMat &allset)

Detailed Description

Definition in file databases.h.

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