The following tutorials demonstrate how effectiveness of cotraining in certain multiview scenarios to boost accuracy over single view methods.


Inference on and visualization of multiview data often requires low-dimensional representations of the data, known as embeddings. Below are tutorials for computing such embeddings on multiview data.


The following tutorials show how to use multi-view decomposition algorithms.


Methods build on top of Matplotlib and Seaborn have been implemented for convenient plotting of multiview data. See examples of such plots on simulated data.

Test Dataset

In order to conviently run tools in this package on multview data, data can be simulated or be accessed from the publicly available UCI multiple features dataset using a dataloader in this package.