Linear Discriminant Analysis.
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#include <opencv2/core.hpp>
Linear Discriminant Analysis.
- Todo
- document this class
◆ LDA() [1/2]
cv::LDA::LDA |
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int | num_components = 0 | ) |
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explicit |
constructor Initializes a LDA with num_components (default 0).
◆ LDA() [2/2]
Initializes and performs a Discriminant Analysis with Fisher's Optimization Criterion on given data in src and corresponding labels in labels. If 0 (or less) number of components are given, they are automatically determined for given data in computation.
◆ ~LDA()
◆ compute()
Compute the discriminants for data in src (row aligned) and labels.
◆ eigenvalues()
Mat cv::LDA::eigenvalues |
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const |
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inline |
Returns the eigenvalues of this LDA.
◆ eigenvectors()
Mat cv::LDA::eigenvectors |
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const |
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inline |
Returns the eigenvectors of this LDA.
◆ lda()
◆ load() [1/2]
◆ load() [2/2]
void cv::LDA::load |
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const String & | filename | ) |
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Deserializes this object from a given filename.
◆ project()
Projects samples into the LDA subspace. src may be one or more row aligned samples.
◆ reconstruct()
Reconstructs projections from the LDA subspace. src may be one or more row aligned projections.
◆ save() [1/2]
void cv::LDA::save |
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const String & | filename | ) |
const |
Serializes this object to a given filename.
◆ save() [2/2]
◆ subspaceProject()
◆ subspaceReconstruct()
◆ _eigenvalues
Mat cv::LDA::_eigenvalues |
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protected |
◆ _eigenvectors
Mat cv::LDA::_eigenvectors |
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protected |
◆ _num_components
int cv::LDA::_num_components |
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protected |
The documentation for this class was generated from the following file: