simCluster and simCluster+

📄️ Bias Detection Report

The Bias Detection Report makes Bias Detection queries for a selected set of variables across all clusters in a model and returns the results in an easy to digest interface for review. The Bias Detection Report is accessed through the Model Actions page for any Supervised Clustering Model.

🗃️ Clustering Insights

4 items

🗃️ simCluster+ Model Specifications

2 items

📄️ simCluster and simCluster+

Clustering

📄️ simCluster and simCluster+ Data Type Specifications

Data Type Specifications tell the model what form the data from each column is in so it knows how to properly compare values.

📄️ simCluster Model Specifications

Model Specifications modify a model's behavior and access to server resources.

📄️ K-Means Versus K-Spilling

simCluster+ uses K-Means as the underlying clustering approach. In general, this means that simCluster+ will return K clusters and every element in the dataset will be mapped to a cluster. However, simCluster can also do K-Spilling clustering. K-Spilling will return K clusters that are more tightly formed around their "mean" centroid, but if a datapoint is not close enough to the centroids, it will "spill" into secondary clusters. This means that K-Spilling will return K+N clusters where the first K are tightly bound and the N additional clusters contain data points that are not within the density criteria.