Commit 16247d62 authored by MONSEIGNE Thibaut's avatar MONSEIGNE Thibaut

Boxes: Pull Request Update Doc

parent 3bfd9844
......@@ -6,7 +6,7 @@ Detailed description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_CovarianceMatrixToFeatureVector_Description|
This box transforms the matrix into a vector for use in a classic classifier.
This box transforms the matrix into a vector for use in a classic classifier. <see cref="Featurization"/> for more details.
* |OVP_DocEnd_BoxAlgorithm_CovarianceMatrixToFeatureVector_Description|
__________________________________________________________________
......@@ -45,7 +45,7 @@ Method of calculating the Feature Vector : \n
* |OVP_DocEnd_BoxAlgorithm_CovarianceMatrixToFeatureVector_Setting1|
* |OVP_DocBegin_BoxAlgorithm_CovarianceMatrixToFeatureVector_Setting2|
Link to the Reference Matrix CSV.
Link to the Reference Matrix CSV. A square matrix of size NxN with N the number of Features. The reference matrix is the same size as the input covariance matrices. The reference matrix is useful for calculating the feature vector on the tangent space.\nRemarks : If no reference an identity matrix is used.
* |OVP_DocEnd_BoxAlgorithm_CovarianceMatrixToFeatureVector_Setting2|
* |OVP_DocBegin_BoxAlgorithm_CovarianceMatrixToFeatureVector_Setting3|
......@@ -65,4 +65,4 @@ __________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_CovarianceMatrixToFeatureVector_Miscellaneous|
* |OVP_DocEnd_BoxAlgorithm_CovarianceMatrixToFeatureVector_Miscellaneous|
*/
*/
\ No newline at end of file
......@@ -6,7 +6,8 @@ Detailed description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_MatrixClassifierProcessor_Description|
Matrix classifier Processor.
Matrix classifier Processor. This box classify input matrix with the loaded classifier model. Actual methods are Minimum Distance to Mean (MDM) and Minimum Distance to Mean with geodesic filtering (FgMDM)\n
<seealso cref="CMatrixClassifierMDM::classify(const Eigen::MatrixXd&, size_t&, std::vector<double>&, std::vector<double>&)"/> <seealso cref="CMatrixClassifierFgMDM::classify(const Eigen::MatrixXd&, size_t&, std::vector<double>&, std::vector<double>&)"/>
* |OVP_DocEnd_BoxAlgorithm_MatrixClassifierProcessor_Description|
__________________________________________________________________
......@@ -67,4 +68,4 @@ __________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_MatrixClassifierProcessor_Miscellaneous|
* |OVP_DocEnd_BoxAlgorithm_MatrixClassifierProcessor_Miscellaneous|
*/
*/
\ No newline at end of file
......@@ -6,7 +6,8 @@ Detailed description
__________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_MatrixClassifierTrainer_Description|
Matrix classifier trainer.
Matrix classifier trainer. This box stack all matrix received in input and launch train function when a stimulation is received. Actual methods are Minimum Distance to Mean (MDM) and Minimum Distance to Mean with geodesic filtering (FgMDM)\n
<seealso cref="CMatrixClassifierMDM::train"/> <seealso cref="CMatrixClassifierFgMDM::train"/>
* |OVP_DocEnd_BoxAlgorithm_MatrixClassifierTrainer_Description|
__________________________________________________________________
......@@ -85,4 +86,4 @@ __________________________________________________________________
* |OVP_DocBegin_BoxAlgorithm_MatrixClassifierTrainer_Miscellaneous|
* |OVP_DocEnd_BoxAlgorithm_MatrixClassifierTrainer_Miscellaneous|
*/
*/
\ No newline at end of file
Time:3x3,End Time,1:,1:,1:,2:,2:,2:,3:,3:,3:,Event Id,Event Date,Event Duration
0.0000000000,0.0000000000, 1.70952664, 0.01674082, 0.02077766, 0.01674082, 1.60344581, 0.05423902, 0.02077766, 0.05423902, 0.8303257,,,
\ No newline at end of file
0.0000000000,0.0000000000, 1.70952664, 0.01674082, 0.02077766, 0.01674082, 1.60344581, 0.05423902, 0.02077766, 0.05423902, 0.8303257,,,
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