Metadata-Version: 2.1
Name: hnne
Version: 0.1.3
Summary: A fast hierarchical dimensionality reduction algorithm.
Home-page: UNKNOWN
Author: Marios Koulakis, Saquib Sarfraz
Author-email: marios.koulakis@gmail.com
License: UNKNOWN
Description: =====
        h-NNE
        =====
        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.
        
        .. code-block:: python
        
          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`_
        
        .. _Basic Usage: notebooks/demo1_basic_usage.ipynb
        .. _Multiple Projections: notebooks/demo2_multiple_projections.ipynb
        .. _Clustering for Free: notebooks/demo3_clustering_for_free.ipynb
        .. _Monitor Class Disentanglement: notebooks/demo4_monitor_class_disentanglement.ipynb
        
        ----------
        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.
        
Keywords: dimension dimensionality reduction t-sne umap hierarchical clustering finch
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: Free for non-commercial use
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/x-rst
