scase 0.1.1

Spectral Embedding Using Deep Neural Networks

ScaSE

ScaSE is a Python package that performs Spectral Embedding with deep neural networks.

This package is based on the following paper - ScaSE

Usage

The basic functionality is quite intuitive and easy to use, e.g.,

from scase import ScaSE

scase = ScaSE(n_components=10) # n_components is the number of dimensions in the low-dimensional representation
scase.fit(X) # X is the dataset and it should be a torch.Tensor
X_reduced = scase.transfrom(X) # Get the low-dimensional representation of the dataset
Y_reduced = scase.transform(Y) # Get the low-dimensional representation of a test dataset

You can read the code docs for more information and functionalities.

Running examples

In order to run the model on the moon dataset, you can either run the file, or using the command-line command:
python -m examples.reduce_moon
This will run the model on the moon dataset and plot the results.

The same can be done for the circles dataset:
python -m examples.reduce_circles