sb_t_svl_res_level Struct Reference

Results of the SVL of a level per model. More...

#include <sb.h>

Collaboration diagram for sb_t_svl_res_level:

Data Fields
float	goodness
	Goodness of the training. More...
float	accuracy
	Accuracy. More...
float	score
	Level score. More...
int	tp
	Number of TRUE POSITIVE samples. More...
int	fp
	Number of FALSE POSITIVE samples. More...
int	tn
	Number of TRUE NEGATIVE samples. More...
int	fn
	Number of FALSE NEGATIVE samples. More...
int	op
	Number of OPTIONAL POSITIVE samples. More...
int	on
	Number of OPTIONAL NEGATIVE samples. More...
int	out_of_roi
	Number of Out Of ROI samples, both optional and required. More...
int	mod_disabled
	Number of samples with disabled model, both optional and required. More...
int	reset
	1 if the SVL of the model has been resetted or when the user reset the SVL, 0 otherwise. More...
int	num_samples_l
	Number of samples of the training dataset used for learning. More...
int	num_samples_t
	Number of samples of the training dataset not used for learning. More...
int	num_img_l
	Number of images of the training dataset used for learning.
sb_t_svl_par_optimization_mode	optimization_mode
	Optimization mode. More...
char	classificator [32]
	Classificator choosen by SVL. More...
char	features [SB_PAR_FEATURES_NAMES_LEN]
	List of the features choosen by SVL. More...
char	features_available [SB_PAR_FEATURES_NAMES_LEN]
	List of the features choosen by user for SVL. More...
char *	warning
	Warning in string format occurred during the training.
sb_t_svl_res_epochs	epochs
	Results of training of module based on Deep Learning. More...

Detailed Description

Results of the SVL of a level per model.

For a Retina project you could write that:

• num_samples_l + num_samples_t = tp + fn + out_of_roi

While for a Surface project you could write that:

• num_samples_l + num_samples_t = tp + fn + tn + out_of_roi

These two formulas are true only if there are no optional out_of_roi samples.
Usually, in Retina project, num_samples_t should be very small if compared to num_samples_l, on the contrary, in Surface projects, num_samples_t is very large because it also counts the background samples, i.e. True Negative samples.

Definition at line 12695 of file sb.h.

Field Documentation

accuracy

float sb_t_svl_res_level::accuracy

Accuracy.

• Retina and Surface projects:
  accuracy = = TP/(TP+FP+FN)
• Deep Surface and Deep Cortex projects:
  In case sb_t_svl_dl_par::save_best is disabled, it is equal to sb_t_svl_res_epoch::accuracy of the last epoch.
  In case sb_t_svl_dl_par::save_best is enabled, it is equal to sb_t_svl_res_epoch::accuracy of the best epoch.

Definition at line 12711 of file sb.h.

classificator

char sb_t_svl_res_level::classificator[32]

Classificator choosen by SVL.

Used only by Retina and Surface projects.

Definition at line 12785 of file sb.h.

epochs

sb_t_svl_res_epochs sb_t_svl_res_level::epochs

Results of training of module based on Deep Learning.

Used only by Deep Surface and Deep Cortex projects.

Definition at line 12806 of file sb.h.

features

char sb_t_svl_res_level::features[SB_PAR_FEATURES_NAMES_LEN]

List of the features choosen by SVL.

The features are separated by the SB_DELIMITER character.
Used only by Retina and Surface projects.

Definition at line 12791 of file sb.h.

features_available

char sb_t_svl_res_level::features_available[SB_PAR_FEATURES_NAMES_LEN]

List of the features choosen by user for SVL.

The features are separated by the SB_DELIMITER character.
Used only by Retina and Surface projects.

Definition at line 12797 of file sb.h.

fn

int sb_t_svl_res_level::fn

Number of FALSE NEGATIVE samples.

Used only by Retina and Surface projects.

Definition at line 12736 of file sb.h.

fp

int sb_t_svl_res_level::fp

Number of FALSE POSITIVE samples.

Used only by Retina and Surface projects.

Definition at line 12726 of file sb.h.

goodness

float sb_t_svl_res_level::goodness

Goodness of the training.

Used only by Retina and Surface projects.

Definition at line 12701 of file sb.h.

mod_disabled

int sb_t_svl_res_level::mod_disabled

Number of samples with disabled model, both optional and required.

Used only by Retina and Surface projects.

Definition at line 12756 of file sb.h.

num_samples_l

int sb_t_svl_res_level::num_samples_l

Number of samples of the training dataset used for learning.

Used only by Retina and Surface projects.

Definition at line 12766 of file sb.h.

num_samples_t

int sb_t_svl_res_level::num_samples_t

Number of samples of the training dataset not used for learning.

Used only by Retina and Surface projects.

Definition at line 12771 of file sb.h.

on

int sb_t_svl_res_level::on

Number of OPTIONAL NEGATIVE samples.

Used only by Retina and Surface projects.

Definition at line 12746 of file sb.h.

op

int sb_t_svl_res_level::op

Number of OPTIONAL POSITIVE samples.

Used only by Retina and Surface projects.

Definition at line 12741 of file sb.h.

optimization_mode

sb_t_svl_par_optimization_mode sb_t_svl_res_level::optimization_mode

Optimization mode.

Used only by Retina and Surface projects.

Definition at line 12780 of file sb.h.

out_of_roi

int sb_t_svl_res_level::out_of_roi

Number of Out Of ROI samples, both optional and required.

Used only by Retina and Surface projects.

Definition at line 12751 of file sb.h.

reset

int sb_t_svl_res_level::reset

1 if the SVL of the model has been resetted or when the user reset the SVL, 0 otherwise.

The value is valid only after sb_svl_run has been called and not after sb_project_load.

Definition at line 12761 of file sb.h.

score

float sb_t_svl_res_level::score

Level score.

Used only by Surface project.

Definition at line 12716 of file sb.h.

tn

int sb_t_svl_res_level::tn

Number of TRUE NEGATIVE samples.

Used only by Retina and Surface projects.

Definition at line 12731 of file sb.h.

tp

int sb_t_svl_res_level::tp

Number of TRUE POSITIVE samples.

Used only by Retina and Surface projects.

Definition at line 12721 of file sb.h.

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The documentation for this struct was generated from the following file:

• sb.h