Struct opencv::core::LDA[][src]

pub struct LDA { /* fields omitted */ }
Expand description

Linear Discriminant Analysis @todo document this class

Implementations

constructor Initializes a LDA with num_components (default 0).

C++ default parameters
  • num_components: 0

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.

C++ default parameters
  • num_components: 0

Trait Implementations

Wrap the specified raw pointer Read more

Return an the underlying raw pointer while consuming this wrapper. Read more

Return the underlying raw pointer. Read more

Return the underlying mutable raw pointer Read more

Executes the destructor for this type. Read more

Deserializes this object from a given filename.

Deserializes this object from a given cv::FileStorage.

Compute the discriminants for data in src (row aligned) and labels.

Projects samples into the LDA subspace. src may be one or more row aligned samples. Read more

Reconstructs projections from the LDA subspace. src may be one or more row aligned projections. Read more

Serializes this object to a given filename.

Serializes this object to a given cv::FileStorage.

Returns the eigenvectors of this LDA.

Returns the eigenvalues of this LDA.

Auto Trait Implementations

Blanket Implementations

Gets the TypeId of self. Read more

Immutably borrows from an owned value. Read more

Mutably borrows from an owned value. Read more

Performs the conversion.

Performs the conversion.

The type returned in the event of a conversion error.

Performs the conversion.

The type returned in the event of a conversion error.

Performs the conversion.