The set of parameters, which controls, how a classifier is being learned from a training set.
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Inherits object.
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| 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.
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| contrast_trigger_default = property |
| | int: Default value for the contrast_trigger.
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| ensemble_size = property |
| | int: Maximum size of the Ensembles of similar instance images to be used for pair feature calculation.
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| ensemble_size_default = property |
| | int: Default value for the ensemble_size.
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| indifference_radius = property |
| | int: Radius (L1 norm!) around a positive instance from which no counter sample is to be extracted.
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| indifference_radius_default = property |
| | int: Default value for the indifference_radius.
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| min_feature_count = property |
| | int: Minimum feature count defining, how many features must be extracted at the very least per class in a classifier.
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| min_feature_count_default = property |
| | int: Default value for the min_feature_count.
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| negative_density = property |
| | float: Density at which counter samples are extracted from the training set images during the learning phase.
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| negative_density_default = property |
| | float: Default value for the negative_density.
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| polydromy = property |
| | int: Polydromy value controlling the complexity of the feature search tree in the classifier.
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| polydromy_default = property |
| | int: Default value for the polydromy.
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The set of parameters, which controls, how a classifier is being learned from a training set.
Instantiates a LearnParameters object.
