LearnParameters Class Reference

The set of parameters, which controls, how a classifier is being learned from a training set. More...

Inherits object.

Properties
	contrast_trigger = property
	int: Minimum gray value difference the two regions of one pair feature must have to be eligible to become a classifier feature. More...
	contrast_trigger_default = property
	int: Default value for the contrast_trigger. More...
	ensemble_size = property
	int: Maximum size of the Ensembles of similar instance images to be used for pair feature calculation. More...
	ensemble_size_default = property
	int: Default value for the ensemble_size. More...
	indifference_radius = property
	int: Radius (L1 norm!) around a positive instance from which no counter sample is to be extracted. More...
	indifference_radius_default = property
	int: Default value for the indifference_radius. More...
	min_feature_count = property
	int: Minimum feature count defining, how many features must be extracted at the very least per class in a classifier. More...
	min_feature_count_default = property
	int: Default value for the min_feature_count. More...
	negative_density = property
	float: Density at which counter samples are extracted from the training set images during the learning phase. More...
	negative_density_default = property
	float: Default value for the negative_density. More...
	polydromy = property
	int: Polydromy value controlling the complexity of the feature search tree in the classifier. More...
	polydromy_default = property
	int: Default value for the polydromy. More...

Detailed Description

The set of parameters, which controls, how a classifier is being learned from a training set.

Instantiates a LearnParameters object.

Property Documentation

contrast_trigger

contrast_trigger = property

static

int: Minimum gray value difference the two regions of one pair feature must have to be eligible to become a classifier feature.

contrast_trigger_default

contrast_trigger_default = property

static

int: Default value for the contrast_trigger.

ensemble_size

ensemble_size = property

static

int: Maximum size of the Ensembles of similar instance images to be used for pair feature calculation.

ensemble_size_default

ensemble_size_default = property

static

int: Default value for the ensemble_size.

indifference_radius

indifference_radius = property

static

int: Radius (L1 norm!) around a positive instance from which no counter sample is to be extracted.

indifference_radius_default

indifference_radius_default = property

static

int: Default value for the indifference_radius.

min_feature_count

min_feature_count = property

static

int: Minimum feature count defining, how many features must be extracted at the very least per class in a classifier.

min_feature_count_default

min_feature_count_default = property

static

int: Default value for the min_feature_count.

negative_density

negative_density = property

static

float: Density at which counter samples are extracted from the training set images during the learning phase.

negative_density_default

negative_density_default = property

static

float: Default value for the negative_density.

polydromy

polydromy = property

static

int: Polydromy value controlling the complexity of the feature search tree in the classifier.

polydromy_default

polydromy_default = property

static

int: Default value for the polydromy.