Percolator.h File Reference

#include <OpenMS/ANALYSIS/ID/PercolatorReset.h>
#include <OpenMS/ANALYSIS/ID/PercolatorTypes.h>
#include <OpenMS/DATASTRUCTURES/DefaultParamHandler.h>
#include <OpenMS/METADATA/PeptideIdentification.h>
#include <OpenMS/METADATA/PeptideIdentificationList.h>
#include <functional>
#include <memory>
#include <utility>
#include <vector>

Go to the source code of this file.

Classes
class	Percolator
	In-process Percolator: semi-supervised target/decoy rescoring with q-values + PEPs. More...
struct	Percolator::CappedTrainingInfo
	The out-of-fold capped training of the last rescore() (subset_mode 'out_of_fold', 'out_of_fold_avg' or 'learning_curve', active). More...

Namespaces
namespace	OpenMS
	Main OpenMS namespace.

---

Class Documentation

OpenMS::Percolator::CappedTrainingInfo

struct OpenMS::Percolator::CappedTrainingInfo

The out-of-fold capped training of the last rescore() (subset_mode 'out_of_fold', 'out_of_fold_avg' or 'learning_curve', active).

Class Members
vector< size_t >	chosen_size	per fold: the sample rows of its kept model
vector< vector< long > >	curve_counts	per size and fold: validation targets (-1: fold had stopped)
vector< vector< long > >	curve_discordant	per size and fold: validation targets accepted by only one of this and the previous size's models (-1: none compared)
vector< size_t >	curve_sizes	training-sample rows of each trained size, in order
vector< int >	fold	per input row: its cross-validation fold, whose model scored it
vector< char >	sampled	per input row: whether it is in a fold model's training set (the sample; learning_curve: of a kept model)
vector< int >	scorer	per input row: the model that scored it (getSvmWeights() index: its fold, or 3 = the average of the fold models)
vector< vector< size_t > >	trained_rows	per fold: the input rows of its model's training set, ascending
size_t	validation_rows = 0	rows of the validation spectra (never trained on)