Class: AffinityPropagation

Perform Affinity Propagation Clustering of data.

Constructors

new AffinityPropagation()

new AffinityPropagation(opts?): AffinityPropagation

Parameters

Parameter	Type	Description
`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.
`opts.convergence_iter`?	`number`	Number of iterations with no change in the number of estimated clusters that stops the convergence.
`opts.copy`?	`boolean`	Make a copy of input data.
`opts.damping`?	`number`	Damping 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).
`opts.max_iter`?	`number`	Maximum number of iterations.
`opts.preference`?	`number` \| [`ArrayLike`	Preferences 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`?	`number`	Pseudo-random number generator to control the starting state. Use an int for reproducible results across function calls. See the Glossary.
`opts.verbose`?	`boolean`	Whether to be verbose.

Returns AffinityPropagation

Defined in generated/cluster/AffinityPropagation.ts:23

Properties

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

Accessors

affinity_matrix_

Get Signature

get affinity_matrix_(): Promise<ArrayLike[]>

Stores the affinity matrix used in fit.

Returns Promise<ArrayLike[]>

Defined in generated/cluster/AffinityPropagation.ts:386

cluster_centers_

Get Signature

get cluster_centers_(): Promise<ArrayLike[]>

Cluster centers (if affinity != precomputed).

Returns Promise<ArrayLike[]>

Defined in generated/cluster/AffinityPropagation.ts:332

cluster_centers_indices_

Get Signature

get cluster_centers_indices_(): Promise<ArrayLike>

Indices of cluster centers.

Returns Promise<ArrayLike>

Defined in generated/cluster/AffinityPropagation.ts:305

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/cluster/AffinityPropagation.ts:467

labels_

Get Signature

get labels_(): Promise<ArrayLike>

Labels of each point.

Returns Promise<ArrayLike>

Defined in generated/cluster/AffinityPropagation.ts:359

n_features_in_

Get Signature

get n_features_in_(): Promise<number>

Number of features seen during fit.

Returns Promise<number>

Defined in generated/cluster/AffinityPropagation.ts:440

n_iter_

Get Signature

get n_iter_(): Promise<number>

Number of iterations taken to converge.

Returns Promise<number>

Defined in generated/cluster/AffinityPropagation.ts:413

py

Get Signature

get py(): PythonBridge

Returns PythonBridge

Set Signature

set py(pythonBridge): void

Parameters

Parameter	Type
`pythonBridge`	`PythonBridge`

Returns void

Defined in generated/cluster/AffinityPropagation.ts:80

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/cluster/AffinityPropagation.ts:136

fit()

fit(opts): Promise<any>

Fit the clustering from features, or affinity matrix.

Parameters

Parameter	Type	Description
`opts`	`object`	-
`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`?	`any`	Not used, present here for API consistency by convention.

Returns Promise<any>

Defined in generated/cluster/AffinityPropagation.ts:153

fit_predict()

fit_predict(opts): Promise<ArrayLike>

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

Parameters

Parameter	Type	Description
`opts`	`object`	-
`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`?	`any`	Not used, present here for API consistency by convention.