Latent Factors
==============
.. figure:: icons/latent-factors.png
Draws data fusion graph with the estimated latent factors overlaid.
Outputs latent factors for further analysis.
Signals
-------
**Inputs**:
- **Fitted fusion graph**
Fitted collective latent data model.
**Outputs**:
- **Relation**
Selected latent data matrix or a completed relation.
Description
-----------
**Latent Factors** widget displays the fusion graph together with the
backbone and recipe matrices estimated by collective matrix
factorization.
Fused data from the widget input are decomposed into latent factors,
which serve as components for subsequent matrix reconstruction. You
would normally draw this widget from **Fusion Graph** and feed its
output (a backbone matrix, a recipe matrix or a completed relation) into
widgets for downstream data analysis, such as **Hierarchial Clustering**
or **Heat Map**.
.. figure:: images/LatentFactors1-stamped.png
1. Information on the input (object types are nodes, data relations are
links between the nodes).
2. A list of **recipe factors** (latent matrices containing compressed
representation of object types). Recipe factors encode latent
components of respective object types.
3. A list of **backbone factors** (latent matrices containing compressed
representation of data relations). Backbone factors encode
interactions between the latent components.
4. A list of **completed relations** (completed relation matrices
obtained by multiplying the corresponding latent matrices).
Example
-------
In the example below we demonstrate how 8 separate
`yeast `__ data sets are fused together in **Fusion Graph**
and then decomposed into latent factors with **Latent Factors** widget.
.. figure:: images/LatentFactors-Example.png