Commands model:power_iteration_clustering/predict

Predict the clusters to which the nodes belong to

POST /v1/commands/

GET /v1/commands/:id

Request

Route

POST /v1/commands/

Body

name:

model:power_iteration_clustering/predict

arguments:

model : Model

Handle of the model to be used

frame : Frame

Frame storing the graph to be clustered

source_column : unicode

Name of the column containing the source node

destination_column : unicode

Name of the column containing the destination node

similarity_column : unicode

Name of the column containing the similarity

k : int32 (default=2)

Number of clusters to cluster the graph into. Default is 2

max_iterations : int32 (default=100)

Maximum number of iterations of the power iteration loop. Default is 100

initialization_mode : unicode (default=random)

Initialization mode of power iteration clustering. This can be either “random” to use a random vector as vertex properties, or “degree” to use normalized sum similarities. Default is “random”.

Headers

Authorization: test_api_key_1
Content-type: application/json

Description

Predict the cluster assignments for the nodes of the graph and create a new frame with a column storing node id and a column with corresponding cluster assignment

Response

Status

200 OK

Body

Returns information about the command. See the Response Body for Get Command here below. It is the same.

GET /v1/commands/:id

Request

Route

GET /v1/commands/18

Body

(None)

Headers

Authorization: test_api_key_1
Content-type: application/json

Response

Status

200 OK

Body

dict

Dictionary containing clustering results | predicted_frame : Frame | A new frame with a column ‘id’ with the node id, and a column ‘cluster’ with the node’s cluster assignment | number_of_clusters : int | Quantity of clusters used | cluster_size : dict | Cluster populations, keyed by names ‘Cluster:1’ through ‘Cluster:n’