Commands graph/ml/belief_propagation

Classification on sparse data using Belief Propagation.

POST /v1/commands/

GET /v1/commands/:id

Request

Route

POST /v1/commands/

Body

name:

graph/ml/belief_propagation

arguments:

graph : <bound method AtkEntityType.__name__ of <trustedanalytics.rest.jsonschema.AtkEntityType object at 0x7f9e68702050>>

<Missing Description>

prior_property : unicode

Name of the vertex property which contains the prior belief for the vertex.

posterior_property : unicode

Name of the vertex property which will contain the posterior belief for each vertex.

edge_weight_property : unicode (default=None)

Name of the edge property that contains the edge weight for each edge.

convergence_threshold : float64 (default=None)

Belief propagation will terminate when the average change in posterior beliefs between supersteps is less than or equal to this threshold.

max_iterations : int32 (default=None)

The maximum number of supersteps that the algorithm will execute. The valid range is all positive int.

Headers

Authorization: test_api_key_1
Content-type: application/json

Description

Belief propagation by the sum-product algorithm. This algorithm analyzes a graphical model with prior beliefs using sum product message passing. The priors are read from a property in the graph, the posteriors are written to another property in the graph. This is the GraphX-based implementation of belief propagation.

See Loopy Belief Propagation for a more in-depth discussion of BP and LBP.

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

Progress report for belief propagation in the format of a multiple-line string.