Partition & Decode: an implicit internal representation framework

Partition & Decode (P&D): a framework that formalizes an implicit internal representation of parametric and nonparametric models, including Deep Networks and Random Forests.

This is preliminary work. More details will be available.

Install from Github

You can manually download partition_decode by cloning the git repo master version and running the setup.py file. That is, unzip the compressed package folder and run the following from the top-level source directory using the terminal::

$ git clone https://github.com/neurodata/partition_decode.git
$ cd partition_decode
$ python3 setup.py install