Documentation
Classes
AffinityPropagation

AffinityPropagation

Perform Affinity Propagation Clustering of data.

Read more in the User Guide.

Python Reference (opens in a new tab)

Constructors

constructor()

Signature

new AffinityPropagation(opts?: object): AffinityPropagation;

Parameters

NameTypeDescription
opts?object-
opts.affinity?"euclidean" | "precomputed"Which affinity to use. At the moment ‘precomputed’ and euclidean are supported. ‘euclidean’ uses the negative squared euclidean distance between points. Default Value 'euclidean'
opts.convergence_iter?numberNumber of iterations with no change in the number of estimated clusters that stops the convergence. Default Value 15
opts.copy?booleanMake a copy of input data. Default Value true
opts.damping?numberDamping factor in the range \0.5, 1.0) is the extent to which the current value is maintained relative to incoming values (weighted 1 - damping). This in order to avoid numerical oscillations when updating these values (messages). Default Value 0.5
opts.max_iter?numberMaximum number of iterations. Default Value 200
opts.preference?number | [ArrayLikePreferences for each point - points with larger values of preferences are more likely to be chosen as exemplars. The number of exemplars, ie of clusters, is influenced by the input preferences value. If the preferences are not passed as arguments, they will be set to the median of the input similarities.
opts.random_state?numberPseudo-random number generator to control the starting state. Use an int for reproducible results across function calls. See the Glossary.
opts.verbose?booleanWhether to be verbose. Default Value false

Returns

AffinityPropagation

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

Properties

_isDisposed

boolean = false

Defined in: generated/cluster/AffinityPropagation.ts:21 (opens in a new tab)

_isInitialized

boolean = false

Defined in: generated/cluster/AffinityPropagation.ts:20 (opens in a new tab)

_py

PythonBridge

Defined in: generated/cluster/AffinityPropagation.ts:19 (opens in a new tab)

id

string

Defined in: generated/cluster/AffinityPropagation.ts:16 (opens in a new tab)

opts

any

Defined in: generated/cluster/AffinityPropagation.ts:17 (opens in a new tab)

Accessors

affinity_matrix_

Stores the affinity matrix used in fit.

Signature

affinity_matrix_(): Promise<ArrayLike[]>;

Returns

Promise<ArrayLike[]>

Defined in: generated/cluster/AffinityPropagation.ts:360 (opens in a new tab)

cluster_centers_

Cluster centers (if affinity != precomputed).

Signature

cluster_centers_(): Promise<ArrayLike[]>;

Returns

Promise<ArrayLike[]>

Defined in: generated/cluster/AffinityPropagation.ts:306 (opens in a new tab)

cluster_centers_indices_

Indices of cluster centers.

Signature

cluster_centers_indices_(): Promise<ArrayLike>;

Returns

Promise<ArrayLike>

Defined in: generated/cluster/AffinityPropagation.ts:279 (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/AffinityPropagation.ts:441 (opens in a new tab)

labels_

Labels of each point.

Signature

labels_(): Promise<ArrayLike>;

Returns

Promise<ArrayLike>

Defined in: generated/cluster/AffinityPropagation.ts:333 (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/AffinityPropagation.ts:414 (opens in a new tab)

n_iter_

Number of iterations taken to converge.

Signature

n_iter_(): Promise<number>;

Returns

Promise<number>

Defined in: generated/cluster/AffinityPropagation.ts:387 (opens in a new tab)

py

Signature

py(): PythonBridge;

Returns

PythonBridge

Defined in: generated/cluster/AffinityPropagation.ts:80 (opens in a new tab)

Signature

py(pythonBridge: PythonBridge): void;

Parameters

NameType
pythonBridgePythonBridge

Returns

void

Defined in: generated/cluster/AffinityPropagation.ts:84 (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/AffinityPropagation.ts:145 (opens in a new tab)

fit()

Fit the clustering from features, or affinity matrix.

Signature

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

Parameters

NameTypeDescription
optsobject-
opts.X?ArrayLike[]Training instances to cluster, or similarities / affinities between instances if affinity='precomputed'. If a sparse feature matrix is provided, it will be converted into a sparse csr\_matrix.
opts.y?anyNot used, present here for API consistency by convention.

Returns

Promise<any>

Defined in: generated/cluster/AffinityPropagation.ts:162 (opens in a new tab)

fit_predict()

Fit clustering from features/affinity matrix; return cluster labels.

Signature

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

Parameters

NameTypeDescription
optsobject-
opts.X?ArrayLike[]Training instances to cluster, or similarities / affinities between instances if affinity='precomputed'. If a sparse feature matrix is provided, it will be converted into a sparse csr\_matrix.
opts.y?anyNot used, present here for API consistency by convention.

Returns

Promise<ArrayLike>

Defined in: generated/cluster/AffinityPropagation.ts:202 (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/AffinityPropagation.ts:93 (opens in a new tab)

predict()

Predict the closest cluster each sample in X belongs to.

Signature

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

Parameters

NameTypeDescription
optsobject-
opts.X?ArrayLikeNew data to predict. If a sparse matrix is provided, it will be converted into a sparse csr\_matrix.

Returns

Promise<ArrayLike>

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