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Weberni69795
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Masterarbeit/openvibe/extras-master/plugins/processing/evaluation/doc/Doc_BoxAlgorithm_ClassifierAccuracyMeasure.dox-part
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/**
* \page BoxAlgorithm_ClassifierAccuracyMeasure Classifier accuracy measure
__________________________________________________________________
Detailed description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_ClassifierAccuracyMeasure_Description|
The real-time classifier accuracies are displayed on vertical progress bars. The accuracy is computed given the results from classifiers, compared to the targets received.
* |OVP_DocEnd_BoxAlgorithm_ClassifierAccuracyMeasure_Description|
__________________________________________________________________
Inputs description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_ClassifierAccuracyMeasure_Inputs|
This box must have at least 2 inputs: one for the targets, and another one for a classifier processor results. User can add more classifier inputs at will.
* |OVP_DocEnd_BoxAlgorithm_ClassifierAccuracyMeasure_Inputs|
* |OVP_DocBegin_BoxAlgorithm_ClassifierAccuracyMeasure_Input1|
The targets the classifier aims at, using stimulation labels.
* |OVP_DocEnd_BoxAlgorithm_ClassifierAccuracyMeasure_Input1|
* |OVP_DocBegin_BoxAlgorithm_ClassifierAccuracyMeasure_Input2|
The classifier results coming from a classifier processor, using stimulation labels.
* |OVP_DocEnd_BoxAlgorithm_ClassifierAccuracyMeasure_Input2|
__________________________________________________________________
Online visualization settings
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_ClassifierAccuracyMeasure_OnlineVisualizationSettings|
Online settings :
Setting1 : Reset scores
Setting2 : Show accuracies as percentages
* |OVP_DocEnd_BoxAlgorithm_ClassifierAccuracyMeasure_OnlineVisualizationSettings|
__________________________________________________________________
Examples description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_ClassifierAccuracyMeasure_Examples|
* |OVP_DocEnd_BoxAlgorithm_ClassifierAccuracyMeasure_Examples|
__________________________________________________________________
Miscellaneous description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_ClassifierAccuracyMeasure_Miscellaneous|
* |OVP_DocEnd_BoxAlgorithm_ClassifierAccuracyMeasure_Miscellaneous|
*/
Masterarbeit/openvibe/extras-master/plugins/processing/evaluation/doc/Doc_BoxAlgorithm_ConfusionMatrix.dox-part
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/**
* \page BoxAlgorithm_ConfusionMatrix Confusion Matrix
__________________________________________________________________
Detailed description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_ConfusionMatrix_Description|
The Confusion Matrix box performs real-time computation of the confusion matrix of a given classifier.
Confusion matrix can be used to measure the performance of a classifier.
The confusion matrix output can be filled with either percentages or values. Optional colum and row can be added to
give the sums of each row and column.
The confusion matrix output can be displayed usig a \ref BoxAlgorithm_MatrixDisplay.
* |OVP_DocEnd_BoxAlgorithm_ConfusionMatrix_Description|
__________________________________________________________________
Inputs description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_ConfusionMatrix_Inputs|
* |OVP_DocEnd_BoxAlgorithm_ConfusionMatrix_Inputs|
* |OVP_DocBegin_BoxAlgorithm_ConfusionMatrix_Input1|
The stimulations that comes from the instruction flow, i.e. the targets that the classifier aims at.
* |OVP_DocEnd_BoxAlgorithm_ConfusionMatrix_Input1|
* |OVP_DocBegin_BoxAlgorithm_ConfusionMatrix_Input2|
The classification results coming from a classifier. These stimulations will be compared to teh target to perform the computation.
* |OVP_DocEnd_BoxAlgorithm_ConfusionMatrix_Input2|
__________________________________________________________________
Outputs description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_ConfusionMatrix_Outputs|
* |OVP_DocEnd_BoxAlgorithm_ConfusionMatrix_Outputs|
* |OVP_DocBegin_BoxAlgorithm_ConfusionMatrix_Output1|
The Confusion matrix.
* |OVP_DocEnd_BoxAlgorithm_ConfusionMatrix_Output1|
__________________________________________________________________
Settings description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_ConfusionMatrix_Settings|
More box settings can be added for a multi class classifier. The default configuration uses 2 classes.
* |OVP_DocEnd_BoxAlgorithm_ConfusionMatrix_Settings|
* |OVP_DocBegin_BoxAlgorithm_ConfusionMatrix_Setting1|
Tells the box to put percentages or values in the matrix.
* |OVP_DocEnd_BoxAlgorithm_ConfusionMatrix_Setting1|
* |OVP_DocBegin_BoxAlgorithm_ConfusionMatrix_Setting2|
If checked, this option adds one row and one column that gives the sums of each row and column in the matrix.
* |OVP_DocEnd_BoxAlgorithm_ConfusionMatrix_Setting2|
* |OVP_DocBegin_BoxAlgorithm_ConfusionMatrix_Setting3|
The stimulation label for the first class.
* |OVP_DocEnd_BoxAlgorithm_ConfusionMatrix_Setting3|
* |OVP_DocBegin_BoxAlgorithm_ConfusionMatrix_Setting4|
The stimulation label for the second class.
* |OVP_DocEnd_BoxAlgorithm_ConfusionMatrix_Setting4|
__________________________________________________________________
Examples description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_ConfusionMatrix_Examples|
* |OVP_DocEnd_BoxAlgorithm_ConfusionMatrix_Examples|
__________________________________________________________________
Miscellaneous description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_ConfusionMatrix_Miscellaneous|
* |OVP_DocEnd_BoxAlgorithm_ConfusionMatrix_Miscellaneous|
*/
Masterarbeit/openvibe/extras-master/plugins/processing/evaluation/doc/Doc_BoxAlgorithm_KappaCoefficient.dox-part
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/**
* \page BoxAlgorithm_KappaCoef Kappa Coefficient
__________________________________________________________________
Detailed description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_KappaCoef_Description|
* This box computes the Cohen kappa coefficient that allows to compare the accordance of two classifiers (https://en.wikipedia.org/wiki/Cohen%27s_kappa),
* The box compares the results of the classifier (second input) to the 100% match classifier (first input).
*
* The result is streamed on the first output, and is displayed in real time in a standalone visualization.
* |OVP_DocEnd_BoxAlgorithm_KappaCoef_Description|
*
*
_______________________________________________________________
Inputs description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_KappaCoef_Inputs|
* |OVP_DocEnd_BoxAlgorithm_KappaCoef_Inputs|
* |OVP_DocBegin_BoxAlgorithm_KappaCoef_Input1|
* The first input receives the expected stimulation.
* |OVP_DocEnd_BoxAlgorithm_KappaCoef_Input1|
* |OVP_DocBegin_BoxAlgorithm_KappaCoef_Input2|
* This input receives the stimualtions found by the classifier.
* |OVP_DocEnd_BoxAlgorithm_KappaCoef_Input2|
__________________________________________________________________
Outputs description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_KappaCoef_Outputs|
* |OVP_DocEnd_BoxAlgorithm_KappaCoef_Outputs|
* |OVP_DocBegin_BoxAlgorithm_KappaCoef_Output1|
* This output contains the current value of the Kappa coefficient.
* |OVP_DocEnd_BoxAlgorithm_KappaCoef_Output1|
__________________________________________________________________
Settings description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_KappaCoef_Settings|
* Each setting except the first one corresponds to the stimulation code of a class. A stimulation must be unique.
* |OVP_DocEnd_BoxAlgorithm_KappaCoef_Settings|
* |OVP_DocBegin_BoxAlgorithm_KappaCoef_Setting1|
* This setting indicates the amount of classes handled by the box. This setting will change the amount of setting.
* |OVP_DocEnd_BoxAlgorithm_KappaCoef_Setting1|
* |OVP_DocBegin_BoxAlgorithm_KappaCoef_Setting2|
* This setting indicates the stimulation corresponding to the first class.
* |OVP_DocEnd_BoxAlgorithm_KappaCoef_Setting2|
*
* * |OVP_DocBegin_BoxAlgorithm_KappaCoef_Setting3|
* This setting indicates the stimulation corresponding to the second class.
* |OVP_DocEnd_BoxAlgorithm_KappaCoef_Setting3|
__________________________________________________________________
Miscellaneous description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_KappaCoef_Miscellaneous|
* All stimulations can be send to the box. They will be filtered.
* |OVP_DocEnd_BoxAlgorithm_KappaCoef_Miscellaneous|
*/
Masterarbeit/openvibe/extras-master/plugins/processing/evaluation/doc/Doc_BoxAlgorithm_ROCCurve.dox-part
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/**
* \page BoxAlgorithm_ROCCurve ROC Curve
__________________________________________________________________
Detailed description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_ROCCurve_Description|
* This box computes the ROC (Receiver Operating Characteristic) curve for a classifier (https://fr.wikipedia.org/wiki/Receiver_Operating_Characteristic). One curve will be computes
* by class. This box is designed to work with the probability output of the \ref Doc_BoxAlgorithm_ClassifierProcessor.
*
* The box will compute the curve when it receives the computation trigger on the first input.
*
* The result is displayed when computed in a standalone visualization.
* |OVP_DocEnd_BoxAlgorithm_ROCCurve_Description|
*
*
_______________________________________________________________
Inputs description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_ROCCurve_Inputs|
* |OVP_DocEnd_BoxAlgorithm_ROCCurve_Inputs|
* |OVP_DocBegin_BoxAlgorithm_ROCCurve_Input1|
The first input receives the expected stimulations stream.
* |OVP_DocEnd_BoxAlgorithm_ROCCurve_Input1|
* |OVP_DocBegin_BoxAlgorithm_ROCCurve_Input2|
This input receives the probability output stream of the processor box.
* |OVP_DocEnd_BoxAlgorithm_ROCCurve_Input2|
__________________________________________________________________
Settings description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_ROCCurve_Settings|
* Each setting after the second one corresponds to the stimulation code of a class. A stimulation must be unique.
* |OVP_DocEnd_BoxAlgorithm_ROCCurve_Settings|
* |OVP_DocBegin_BoxAlgorithm_ROCCurve_Setting1|
* Stimulation trigger for the computation.
* |OVP_DocEnd_BoxAlgorithm_ROCCurve_Setting1|
* |OVP_DocBegin_BoxAlgorithm_ROCCurve_Setting2|
* This setting indicates the amount of classes handled by the box. This setting will change the amount of setting.
* |OVP_DocEnd_BoxAlgorithm_ROCCurve_Setting2|
* |OVP_DocBegin_BoxAlgorithm_ROCCurve_Setting3|
* This setting indicates the stimulation corresponding to the first class.
* |OVP_DocEnd_BoxAlgorithm_ROCCurve_Setting3|
*
* * |OVP_DocBegin_BoxAlgorithm_ROCCurve_Setting4|
* This setting indicates the stimulation corresponding to the second class.
* |OVP_DocEnd_BoxAlgorithm_ROCCurve_Setting4|
__________________________________________________________________
Miscellaneous description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_ROCCurve_Miscellaneous|
* All stimulations can be send to the box. They will be filtered.
* |OVP_DocEnd_BoxAlgorithm_ROCCurve_Miscellaneous|
*/
Masterarbeit/openvibe/extras-master/plugins/processing/evaluation/doc/Doc_BoxAlgorithm_StatisticGenerator.dox-part
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/**
* \page BoxAlgorithm_GeneralStatisticsGenerator General Statistic Generator
__________________________________________________________________
Detailed description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_GeneralStatisticsGenerator_Description|
* The box analyses a the two input stream (stimulations and signal).
*
* The box will provide for each channel of the signal the min, the max value and the mean.
* The box will provide a list of stimulations and provide for them the amount of time they appeared.
*
* |OVP_DocEnd_BoxAlgorithm_GeneralStatisticsGenerator_Description|
__________________________________________________________________
Inputs description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_GeneralStatisticsGenerator_Inputs|
* |OVP_DocEnd_BoxAlgorithm_GeneralStatisticsGenerator_Inputs|
* |OVP_DocBegin_BoxAlgorithm_GeneralStatisticsGenerator_Input1|
* The signal stream to analyse.
* |OVP_DocEnd_BoxAlgorithm_GeneralStatisticsGenerator_Input1|
*
* |OVP_DocBegin_BoxAlgorithm_GeneralStatisticsGenerator_Input2|
* The stimulation stream to analyse.
* |OVP_DocEnd_BoxAlgorithm_GeneralStatisticsGenerator_Input2|
__________________________________________________________________
Settings description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_GeneralStatisticsGenerator_Settings|
* |OVP_DocEnd_BoxAlgorithm_GeneralStatisticsGenerator_Settings|
* |OVP_DocBegin_BoxAlgorithm_GeneralStatisticsGenerator_Setting1|
* Path to the file where the results will be wrote.
* |OVP_DocEnd_BoxAlgorithm_GeneralStatisticsGenerator_Setting1|
__________________________________________________________________
Examples description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_GeneralStatisticsGenerator_Examples|
* The resulting file should look like this :
\verbatim
<Statistic>
<Stimulations-list>
<Stimulation>
<Identifier>(0x00000000, 0x00008100)</Identifier>
<Label>OVTK_StimulationId_Label_00</Label>
<Count>500</Count>
</Stimulation>
</Stimulations-list>
<Channel-list>
<Channel>
<Name>sinusOsc 1</Name>
<Maximum>2.99595</Maximum>
<Minimum>-2.99582</Minimum>
<Mean>0.00374409</Mean>
</Channel>
<Channel>
<Name>sinusOsc 2</Name>
<Maximum>2.99555</Maximum>
<Minimum>-2.99594</Minimum>
<Mean>0.00215169</Mean>
</Channel>
<Channel>
<Name>sinusOsc 3</Name>
<Maximum>2.99594</Maximum>
<Minimum>-2.99592</Minimum>
<Mean>0.000474523</Mean>
</Channel>
<Channel>
<Name>sinusOsc 4</Name>
<Maximum>2.99591</Maximum>
<Minimum>-2.99594</Minimum>
<Mean>0.00127219</Mean>
</Channel>
</Channel-list>
</Statistic>
\endverbatim
* |OVP_DocEnd_BoxAlgorithm_GeneralStatisticsGenerator_Examples|
__________________________________________________________________
Miscellaneous description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_KappaCoef_Miscellaneous|
* |OVP_DocEnd_BoxAlgorithm_KappaCoef_Miscellaneous|
*
*/