simCluster Model Specifications

simSearch K

Specify the K number of results for the nearest neighbor search. (Default 10)

Pivots

The number of primary search points in the engine. This may improve query speed at the cost of training time. (Range 256 to 1024, default 256)

Probability

Minimum accepted probability that the distance between the result and the query will be within the Accepted Error range.  Any result with lower probability will be discarded. (Range 0 to 1, default .95)

Accepted Error

Maximum accepted difference in distance between returned objects and the query object. (Minimum 1, default 1.2)

simCluster Range

Maximum accepted distance between the center of a cluster and a given element. (Range 0 to 1, default .2)

simCluster Iterations

Number of passes taken by simCluster to identify new cluster centers. (Minimum 1, default 3)

simCluster Percentage

Proportion of elements used to identify cluster centers for each pass. Higher may result in more granular clusters. (Range 0 to 1, default .5)

Processing Recipe

Determines if the clustering will be supervised or unsupervised. Dense = Supervised, Universal = Unsupervised. Dense requires a Class column to be specified.