Struct opencv::core::LDA

source ·
pub struct LDA { /* private fields */ }
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.
Reconstructs projections from the LDA subspace. src may be one or more row aligned projections.
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

Returns the argument unchanged.

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

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.