Struct linfa_reduction::DiffusionMap
source · [−]pub struct DiffusionMap<F> { /* private fields */ }
Expand description
Embedding of diffusion map technique
After transforming the dataset with diffusion map this structure store the embedding for further use. No straightforward prediction can be made from the embedding and the algorithm falls therefore in the class of transformers.
The diffusion map computes an embedding of the data by applying PCA on the diffusion operator of the data. It transforms the data along the direction of the largest diffusion flow and is therefore a non-linear dimensionality reduction technique. A normalized kernel describes the high dimensional diffusion graph with the (i, j) entry the probability that a diffusion happens from point i to j.
Example
use linfa::traits::Transformer;
use linfa_kernel::{Kernel, KernelType, KernelMethod};
use linfa_reduction::DiffusionMap;
let dataset = linfa_datasets::iris();
// generate sparse gaussian kernel with eps = 2 and 15 neighbors
let kernel = Kernel::params()
.kind(KernelType::Sparse(15))
.method(KernelMethod::Gaussian(2.0))
.transform(dataset.records());
// create embedding from kernel matrix using diffusion maps
let mapped_kernel = DiffusionMap::<f64>::params(2)
.steps(1)
.transform(&kernel)
.unwrap();
// get embedding from the transformed kernel matrix
let embedding = mapped_kernel.embedding();
Implementations
sourceimpl<F: Float> DiffusionMap<F>
impl<F: Float> DiffusionMap<F>
sourceimpl<F> DiffusionMap<F>
impl<F> DiffusionMap<F>
pub fn params(embedding_size: usize) -> DiffusionMapParams
Trait Implementations
sourceimpl<F: Clone> Clone for DiffusionMap<F>
impl<F: Clone> Clone for DiffusionMap<F>
sourcefn clone(&self) -> DiffusionMap<F>
fn clone(&self) -> DiffusionMap<F>
Returns a copy of the value. Read more
1.0.0 · sourcefn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
Performs copy-assignment from source
. Read more
sourceimpl<F: Debug> Debug for DiffusionMap<F>
impl<F: Debug> Debug for DiffusionMap<F>
sourceimpl<F: PartialEq> PartialEq<DiffusionMap<F>> for DiffusionMap<F>
impl<F: PartialEq> PartialEq<DiffusionMap<F>> for DiffusionMap<F>
sourcefn eq(&self, other: &DiffusionMap<F>) -> bool
fn eq(&self, other: &DiffusionMap<F>) -> bool
This method tests for self
and other
values to be equal, and is used
by ==
. Read more
sourcefn ne(&self, other: &DiffusionMap<F>) -> bool
fn ne(&self, other: &DiffusionMap<F>) -> bool
This method tests for !=
.
sourceimpl<'a, F: Float> Transformer<&'a KernelBase<ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>, CsMatBase<F, usize, Vec<usize, Global>, Vec<usize, Global>, Vec<F, Global>, usize>>, DiffusionMap<F>> for DiffusionMapValidParams
impl<'a, F: Float> Transformer<&'a KernelBase<ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>, CsMatBase<F, usize, Vec<usize, Global>, Vec<usize, Global>, Vec<F, Global>, usize>>, DiffusionMap<F>> for DiffusionMapValidParams
impl<F> StructuralPartialEq for DiffusionMap<F>
Auto Trait Implementations
impl<F> RefUnwindSafe for DiffusionMap<F> where
F: RefUnwindSafe,
impl<F> Send for DiffusionMap<F> where
F: Send,
impl<F> Sync for DiffusionMap<F> where
F: Sync,
impl<F> Unpin for DiffusionMap<F>
impl<F> UnwindSafe for DiffusionMap<F> where
F: RefUnwindSafe,
Blanket Implementations
sourceimpl<T> BorrowMut<T> for T where
T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
const: unstable · sourcefn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more