Class: LocallyLinearEmbedding

Locally Linear Embedding.

Constructors

new LocallyLinearEmbedding()

new LocallyLinearEmbedding(opts?): LocallyLinearEmbedding

Parameters

Parameter	Type	Description
`opts`?	`object`	-
`opts.eigen_solver`?	`"auto"` \| `"arpack"` \| `"dense"`	The solver used to compute the eigenvectors. The available options are:
`opts.hessian_tol`?	`number`	Tolerance for Hessian eigenmapping method. Only used if `method \== 'hessian'`.
`opts.max_iter`?	`number`	Maximum number of iterations for the arpack solver. Not used if eigen_solver==’dense’.
`opts.method`?	`"standard"` \| `"hessian"` \| `"modified"` \| `"ltsa"`	`standard`: use the standard locally linear embedding algorithm. see reference [1]
`opts.modified_tol`?	`number`	Tolerance for modified LLE method. Only used if `method \== 'modified'`.
`opts.n_components`?	`number`	Number of coordinates for the manifold.
`opts.n_jobs`?	`number`	The number of parallel jobs to run. `undefined` means 1 unless in a `joblib.parallel_backend` context. `\-1` means using all processors. See Glossary for more details.
`opts.n_neighbors`?	`number`	Number of neighbors to consider for each point.
`opts.neighbors_algorithm`?	`"auto"` \| `"ball_tree"` \| `"kd_tree"` \| `"brute"`	Algorithm to use for nearest neighbors search, passed to `NearestNeighbors` instance.
`opts.random_state`?	`number`	Determines the random number generator when `eigen_solver` == ‘arpack’. Pass an int for reproducible results across multiple function calls. See Glossary.
`opts.reg`?	`number`	Regularization constant, multiplies the trace of the local covariance matrix of the distances.
`opts.tol`?	`number`	Tolerance for ‘arpack’ method Not used if eigen_solver==’dense’.

Returns LocallyLinearEmbedding

Defined in generated/manifold/LocallyLinearEmbedding.ts:23

Properties

Property	Type	Default value	Defined in
`_isDisposed`	`boolean`	`false`	generated/manifold/LocallyLinearEmbedding.ts:21
`_isInitialized`	`boolean`	`false`	generated/manifold/LocallyLinearEmbedding.ts:20
`_py`	`PythonBridge`	`undefined`	generated/manifold/LocallyLinearEmbedding.ts:19
`id`	`string`	`undefined`	generated/manifold/LocallyLinearEmbedding.ts:16
`opts`	`any`	`undefined`	generated/manifold/LocallyLinearEmbedding.ts:17

Accessors

embedding_

Get Signature

get embedding_(): Promise<ArrayLike>

Stores the embedding vectors

Returns Promise<ArrayLike>

Defined in generated/manifold/LocallyLinearEmbedding.ts:411

feature_names_in_

Get Signature

get feature_names_in_(): Promise<ArrayLike>

Names of features seen during fit. Defined only when X has feature names that are all strings.

Returns Promise<ArrayLike>

Defined in generated/manifold/LocallyLinearEmbedding.ts:492

n_features_in_

Get Signature

get n_features_in_(): Promise<number>

Number of features seen during fit.

Returns Promise<number>

Defined in generated/manifold/LocallyLinearEmbedding.ts:465

nbrs_

Get Signature

get nbrs_(): Promise<any>

Stores nearest neighbors instance, including BallTree or KDtree if applicable.

Returns Promise<any>

Defined in generated/manifold/LocallyLinearEmbedding.ts:519

py

Get Signature

get py(): PythonBridge

Returns PythonBridge

Set Signature

set py(pythonBridge): void

Parameters

Parameter	Type
`pythonBridge`	`PythonBridge`

Returns void

Defined in generated/manifold/LocallyLinearEmbedding.ts:108

reconstruction_error_

Get Signature

get reconstruction_error_(): Promise<number>

Reconstruction error associated with embedding_

Returns Promise<number>

Defined in generated/manifold/LocallyLinearEmbedding.ts:438

Methods

dispose()

dispose(): Promise<void>

Disposes of the underlying Python resources.

Once dispose() is called, the instance is no longer usable.

Returns Promise<void>

Defined in generated/manifold/LocallyLinearEmbedding.ts:164

fit()

fit(opts): Promise<any>

Compute the embedding vectors for data X.

Parameters

Parameter	Type	Description
`opts`	`object`	-
`opts.X`?	`ArrayLike`[]	Training set.
`opts.y`?	`any`	Not used, present here for API consistency by convention.

Returns Promise<any>

Defined in generated/manifold/LocallyLinearEmbedding.ts:181

fit_transform()

fit_transform(opts): Promise<ArrayLike>

Compute the embedding vectors for data X and transform X.

Parameters

Parameter	Type	Description
`opts`	`object`	-
`opts.X`?	`ArrayLike`[]	Training set.
`opts.y`?	`any`	Not used, present here for API consistency by convention.

Returns Promise<ArrayLike>

Defined in generated/manifold/LocallyLinearEmbedding.ts:220

get_feature_names_out()

get_feature_names_out(opts): Promise<any>

Get output feature names for transformation.

The feature names out will prefixed by the lowercased class name. For example, if the transformer outputs 3 features, then the feature names out are: \["class_name0", "class_name1", "class_name2"\].

Parameters