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SpectralCoclustering

SpectralCoclustering

Spectral Co-Clustering algorithm (Dhillon, 2001).

Clusters rows and columns of an array X to solve the relaxed normalized cut of the bipartite graph created from X as follows: the edge between row vertex i and column vertex j has weight X\[i, j\].

The resulting bicluster structure is block-diagonal, since each row and each column belongs to exactly one bicluster.

Supports sparse matrices, as long as they are nonnegative.

Read more in the User Guide.

Python Reference (opens in a new tab)

Constructors

constructor()

Signature

new SpectralCoclustering(opts?: object): SpectralCoclustering;

Parameters

NameTypeDescription
opts?object-
opts.init?ArrayLike[]Method for initialization of k-means algorithm; defaults to ‘k-means++’. Default Value 'k-means++'
opts.mini_batch?booleanWhether to use mini-batch k-means, which is faster but may get different results. Default Value false
opts.n_clusters?numberThe number of biclusters to find. Default Value 3
opts.n_init?numberNumber of random initializations that are tried with the k-means algorithm. If mini-batch k-means is used, the best initialization is chosen and the algorithm runs once. Otherwise, the algorithm is run for each initialization and the best solution chosen. Default Value 10
opts.n_svd_vecs?numberNumber of vectors to use in calculating the SVD. Corresponds to ncv when svd\_method=arpack and n\_oversamples when svd\_method is ‘randomized`.
opts.random_state?numberUsed for randomizing the singular value decomposition and the k-means initialization. Use an int to make the randomness deterministic. See Glossary.
opts.svd_method?"randomized" | "arpack"Selects the algorithm for finding singular vectors. May be ‘randomized’ or ‘arpack’. If ‘randomized’, use sklearn.utils.extmath.randomized\_svd, which may be faster for large matrices. If ‘arpack’, use scipy.sparse.linalg.svds (opens in a new tab), which is more accurate, but possibly slower in some cases. Default Value 'randomized'

Returns

SpectralCoclustering

Defined in: generated/cluster/SpectralCoclustering.ts:29 (opens in a new tab)

Methods

dispose()

Disposes of the underlying Python resources.

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

Signature

dispose(): Promise<void>;

Returns

Promise<void>

Defined in: generated/cluster/SpectralCoclustering.ts:146 (opens in a new tab)

fit()

Create a biclustering for X.

Signature

fit(opts: object): Promise<any>;

Parameters

NameTypeDescription
optsobject-
opts.X?ArrayLike[]Training data.
opts.y?anyNot used, present for API consistency by convention.

Returns

Promise<any>

Defined in: generated/cluster/SpectralCoclustering.ts:163 (opens in a new tab)

get_indices()

Row and column indices of the i’th bicluster.

Only works if rows\_ and columns\_ attributes exist.

Signature

get_indices(opts: object): Promise<ArrayLike>;

Parameters

NameTypeDescription
optsobject-
opts.i?numberThe index of the cluster.

Returns

Promise<ArrayLike>

Defined in: generated/cluster/SpectralCoclustering.ts:205 (opens in a new tab)

get_metadata_routing()

Get metadata routing of this object.

Please check User Guide on how the routing mechanism works.

Signature

get_metadata_routing(opts: object): Promise<any>;

Parameters

NameTypeDescription
optsobject-
opts.routing?anyA MetadataRequest encapsulating routing information.

Returns

Promise<any>

Defined in: generated/cluster/SpectralCoclustering.ts:244 (opens in a new tab)

get_shape()

Shape of the i’th bicluster.

Signature

get_shape(opts: object): Promise<number>;

Parameters

NameTypeDescription
optsobject-
opts.i?numberThe index of the cluster.

Returns

Promise<number>

Defined in: generated/cluster/SpectralCoclustering.ts:282 (opens in a new tab)

get_submatrix()

Return the submatrix corresponding to bicluster i.

Signature

get_submatrix(opts: object): Promise<ArrayLike[]>;

Parameters

NameTypeDescription
optsobject-
opts.data?ArrayLike[]The data.
opts.i?numberThe index of the cluster.

Returns

Promise<ArrayLike[]>

Defined in: generated/cluster/SpectralCoclustering.ts:319 (opens in a new tab)

init()

Initializes the underlying Python resources.

This instance is not usable until the Promise returned by init() resolves.

Signature

init(py: PythonBridge): Promise<void>;

Parameters

NameType
pyPythonBridge

Returns

Promise<void>

Defined in: generated/cluster/SpectralCoclustering.ts:94 (opens in a new tab)

Properties

_isDisposed

boolean = false

Defined in: generated/cluster/SpectralCoclustering.ts:27 (opens in a new tab)

_isInitialized

boolean = false

Defined in: generated/cluster/SpectralCoclustering.ts:26 (opens in a new tab)

_py

PythonBridge

Defined in: generated/cluster/SpectralCoclustering.ts:25 (opens in a new tab)

id

string

Defined in: generated/cluster/SpectralCoclustering.ts:22 (opens in a new tab)

opts

any

Defined in: generated/cluster/SpectralCoclustering.ts:23 (opens in a new tab)

Accessors

column_labels_

The bicluster label of each column.

Signature

column_labels_(): Promise<ArrayLike>;

Returns

Promise<ArrayLike>

Defined in: generated/cluster/SpectralCoclustering.ts:444 (opens in a new tab)

columns_

Results of the clustering, like rows.

Signature

columns_(): Promise<ArrayLike[]>;

Returns

Promise<ArrayLike[]>

Defined in: generated/cluster/SpectralCoclustering.ts:390 (opens in a new tab)

feature_names_in_

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

Signature

feature_names_in_(): Promise<ArrayLike>;

Returns

Promise<ArrayLike>

Defined in: generated/cluster/SpectralCoclustering.ts:498 (opens in a new tab)

n_features_in_

Number of features seen during fit.

Signature

n_features_in_(): Promise<number>;

Returns

Promise<number>

Defined in: generated/cluster/SpectralCoclustering.ts:471 (opens in a new tab)

py

Signature

py(): PythonBridge;

Returns

PythonBridge

Defined in: generated/cluster/SpectralCoclustering.ts:81 (opens in a new tab)

Signature

py(pythonBridge: PythonBridge): void;

Parameters

NameType
pythonBridgePythonBridge

Returns

void

Defined in: generated/cluster/SpectralCoclustering.ts:85 (opens in a new tab)

row_labels_

The bicluster label of each row.

Signature

row_labels_(): Promise<ArrayLike>;

Returns

Promise<ArrayLike>

Defined in: generated/cluster/SpectralCoclustering.ts:417 (opens in a new tab)

rows_

Results of the clustering. rows\[i, r\] is true if cluster i contains row r. Available only after calling fit.

Signature

rows_(): Promise<ArrayLike[]>;

Returns

Promise<ArrayLike[]>

Defined in: generated/cluster/SpectralCoclustering.ts:363 (opens in a new tab)