The set of parameters, which controls, how a classifier is being learned from a training set.
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#include <cvb/minos/learn_parameters.hpp>
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int | MinFeatureCount () const noexcept |
| Gets the minimum feature count defining, how many features must be extracted at the very least per class in a classifier. More...
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void | SetMinFeatureCount (int minFeatureCount) |
| Sets the minimum feature count defining, how many features must be extracted at the very least per class in a classifier. More...
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int | Polydromy () const noexcept |
| Gets the polydromy value controlling the complexity of the feature search tree in the classifier. More...
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void | SetPolydromy (int polydromy) |
| Sets the polydromy value controlling the complexity of the feature search tree in the classifier. Valid polydromy values must be greater than 0, the default value is 2. More...
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int | EnsembleSize () const noexcept |
| Gets the maximum size of the Ensembles of similar instance images to be used for pair feature calculation. More...
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void | SetEnsembleSize (int ensembleSize) |
| Sets the maximum size of the Ensembles of similar instance images to be used for pair feature calculation. Valid ensemble sizes must be greater than 0, the default value is 15. More...
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int | ContrastTrigger () const noexcept |
| Gets the minimum gray value difference the two regions of one pair feature must have to be eligible to become a classifier feature. More...
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void | SetContrastTrigger (int contrastTrigger) |
| Sets the minimum gray value difference the two regions of one pair feature must have to be eligible to become a classifier feature. Valid contrast triggers must be greater than 0, the default value is 8. More...
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int | IndifferenceRadius () const noexcept |
| Gets the radius (L1 norm!) around a positive instance from which no counter sample is to be extracted. More...
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void | SetIndifferenceRadius (int indifferenceRadius) |
| Sets the radius (L1 norm!) around a positive instance from which no counter sample is to be extracted. Valid indifference radii must be greater than 0. The default value is 6 here. More...
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double | NegativeDensity () const noexcept |
| Gets the density at which counter samples are extracted from the training set images during the learning phase. More...
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void | SetNegativeDensity (double negativeDensity) |
| Sets the density at which counter samples are extracted from the training set images during the learning phase. Valid negative densities range from 0.0 to 1.0. The default value is 1.0. More...
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The set of parameters, which controls, how a classifier is being learned from a training set.
◆ ContrastTrigger()
int ContrastTrigger |
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const |
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inlinenoexcept |
Gets the minimum gray value difference the two regions of one pair feature must have to be eligible to become a classifier feature.
- Returns
- The contrast trigger value.
- Exceptions
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Does | not throw any exception. |
◆ ContrastTriggerDefault()
static int ContrastTriggerDefault |
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inlinestaticnoexcept |
Default value for the ContrastTrigger.
- Returns
- Default constrast trigger value.
- Exceptions
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Does | not throw any exception. |
◆ EnsembleSize()
int EnsembleSize |
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const |
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inlinenoexcept |
Gets the maximum size of the Ensembles of similar instance images to be used for pair feature calculation.
- Returns
- The ensemble size value.
- Exceptions
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Does | not throw any exception. |
◆ EnsembleSizeDefault()
static int EnsembleSizeDefault |
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inlinestaticnoexcept |
Default value for the EnsembleSize.
- Returns
- Default ensemble size value.
- Exceptions
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Does | not throw any exception. |
◆ IndifferenceRadius()
int IndifferenceRadius |
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const |
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inlinenoexcept |
Gets the radius (L1 norm!) around a positive instance from which no counter sample is to be extracted.
- Returns
- The indifference radius value.
- Exceptions
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Does | not throw any exception. |
◆ IndifferenceRadiusDefault()
static int IndifferenceRadiusDefault |
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inlinestaticnoexcept |
Default value for the IndifferenceRadius.
- Returns
- Default indeference radius value.
- Exceptions
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Does | not throw any exception. |
◆ MinFeatureCount()
int MinFeatureCount |
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const |
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inlinenoexcept |
Gets the minimum feature count defining, how many features must be extracted at the very least per class in a classifier.
- Returns
- The minimum feature count.
- Exceptions
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Does | not throw any exception. |
◆ MinFeatureCountDefault()
static int MinFeatureCountDefault |
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inlinestaticnoexcept |
Default value for the MinFeatureCount.
- Returns
- Default min feature count value.
- Exceptions
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Does | not throw any exception. |
◆ NegativeDensity()
double NegativeDensity |
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const |
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inlinenoexcept |
Gets the density at which counter samples are extracted from the training set images during the learning phase.
- Returns
- The negative density value.
- Exceptions
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Does | not throw any exception. |
◆ NegativeDensityDefault()
static double NegativeDensityDefault |
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inlinestaticnoexcept |
Default value for the NegativeDensity.
- Returns
- Default negative density value.
- Exceptions
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Does | not throw any exception. |
◆ Polydromy()
Gets the polydromy value controlling the complexity of the feature search tree in the classifier.
- Returns
- The polydromy value.
- Exceptions
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Does | not throw any exception. |
◆ PolydromyDefault()
static int PolydromyDefault |
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inlinestaticnoexcept |
Default value for the Polydromy.
- Returns
- Default polydromy value.
- Exceptions
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Does | not throw any exception. |
◆ SetContrastTrigger()
void SetContrastTrigger |
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int |
contrastTrigger | ) |
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inline |
Sets the minimum gray value difference the two regions of one pair feature must have to be eligible to become a classifier feature. Valid contrast triggers must be greater than 0, the default value is 8.
- Parameters
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[in] | contrastTrigger | The contrast trigger value. |
- Exceptions
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Does | not throw any exception. |
◆ SetEnsembleSize()
void SetEnsembleSize |
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int |
ensembleSize | ) |
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inline |
Sets the maximum size of the Ensembles of similar instance images to be used for pair feature calculation. Valid ensemble sizes must be greater than 0, the default value is 15.
- Parameters
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[in] | ensembleSize | The ensemble size value. |
- Exceptions
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Does | not throw any exception. |
◆ SetIndifferenceRadius()
void SetIndifferenceRadius |
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int |
indifferenceRadius | ) |
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inline |
Sets the radius (L1 norm!) around a positive instance from which no counter sample is to be extracted. Valid indifference radii must be greater than 0. The default value is 6 here.
- Parameters
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[in] | indifferenceRadius | The indifference radius value. |
- Exceptions
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Does | not throw any exception. |
◆ SetMinFeatureCount()
void SetMinFeatureCount |
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int |
minFeatureCount | ) |
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inline |
Sets the minimum feature count defining, how many features must be extracted at the very least per class in a classifier.
- Parameters
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[in] | minFeatureCount | The minimum feature count. |
- Exceptions
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Does | not throw any exception. |
◆ SetNegativeDensity()
void SetNegativeDensity |
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double |
negativeDensity | ) |
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inline |
Sets the density at which counter samples are extracted from the training set images during the learning phase. Valid negative densities range from 0.0 to 1.0. The default value is 1.0.
- Parameters
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[in] | negativeDensity | The negative density value. |
- Exceptions
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Does | not throw any exception. |
◆ SetPolydromy()
void SetPolydromy |
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int |
polydromy | ) |
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inline |
Sets the polydromy value controlling the complexity of the feature search tree in the classifier. Valid polydromy values must be greater than 0, the default value is 2.
- Parameters
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[in] | polydromy | The polydromy value. |
- Exceptions
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Does | not throw any exception. |