Completion Scoring ================== .. figure:: icons/completion-scoring.png Scores the quality of matrix completion using root mean squared error (RSME) metric. Signals ------- **Inputs**: - **Fitted fusion graph** Fitted collective latent data model. - **Relation** Relationships between two groups of objects. **Outputs**: - (None) Description ----------- This widget assesses the quality of matrix completion based on root mean squared error metric (`RMSE `__). Each row contains scores representing matrix completion quality of different relations. Results for prediction models are in columns. .. figure:: images/CompletionScoring-stamped.png 1. The RMSE value chart for the input relation matrix. Example ------- **Completion Scoring** widget assesses the quality of matrix completion using the RMSE metric. Connect it with **Matrix Sampler** to score prediction models (previously learnt on in-sample data) on out-of-the-sample data. You can also use **Mean Fuser** to get a mean score for latent values. .. figure:: images/CompletionScoring-Example.png