Technical User Reference (Clustering)
This section details the ModelClass and logics that the Clustering Accelerator deploys. For each step, its aim, outputs, and the main reasons to modify the logics are explained.
In this section:
Â
Clustering Model Class
The Clustering ModelClass organizes a list of logics to create the model architecture. It is a JSON file that refers to some logics and it is transformed into an optimized UI in the Pricefx platform.
The general architecture of the Negotiation Guidance Model Class is:
It defines four steps
Definition – Sets the scope of the transactions.
Configuration – Sets the parameters for the clustering.
Results – Looks at the outputs of the clustering, the properties of the clusters and eventually how to change the configuration toward a better clustering.
Export – Copies the result of the clustering into a Data Source.
Library
The logic is Clustering_Library.
Definition Step
There is no calculation logic in this step, and there is one tab with related evaluation logics: Clustering_defnition_eval and Clustering_defnition_eval_configurator.
Model Configuration Step
Contains one calculation logic Clustering_configuration_calc that executes when accessing this step and one tab split in two panels, one for user inputs, the other for evaluation.
Calculation: PriceDrivers
The logic is Clustering_configuration_calc.
Setup Panel
The logic is Clustering_configuration_configurator.
EvaluationPanel
The logic is Clustering_configuration_dimensions.
Result Step
Contains one calculation logic Clustering_clustering_calc that is executed when accessing this step and one tab split in four tabs: Overview, Details (Group by), and Details.
Overview
The logics are Clustering_result_matrix and Clustering_result_pca.
Details (Group by)
The logic is Clustering_expense_matrix.
Details
The logic is Clustering_metrics.
Export Step
Contains two calculation logics Clustering_export_createDS and Clustering_export_feedDS.
Evaluations
The model has one evaluation: Clustering_api_CustomerCluster
. For more details about model evaluations see Query Optimization Engine Results | Using the Evaluator.