hnne 0.1.3

A fast hierarchical dimensionality reduction algorithm.

A fast hierarchical dimensionality reduction algorithm.

Installation

The project is available in PyPI. To install run:

pip install hnne

How to use h-NNE

The main class implements the main methods of the sklearn interface.

import numpy as np
from hnne import HNNE

data = np.random.rand()

projector = HNNE()
projection = projector.fit_transform(data)

Demos

The following demo notebooks are available:

1. Basic Usage

2. Multiple Projections

3. Clustering for Free

4. Monitor Class Disentanglement

References

If you make use of this project in your work, please cite the following references:

[1] M. Saquib Sarfraz*, Marios Koulakis*, Constantin Seibold, Rainer Stiefelhagen.

Hierarchical Nearest Neighbor Graph Embedding for Efficient Dimensionality Reduction.

[2] Sarfraz, Saquib and Sharma, Vivek and Stiefelhagen, Rainer. Efficient Parameter-Free Clustering

Using First Neighbor Relations. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). June 2019.