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