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Geometric Machine Learning Algorithms

Here are some geometric machine learning algorithms I wrote.

These packages/libraries are used throughout this repository:

  1. scikit learn
  2. networkx
  3. numpy
  4. matplotlib
  5. pandas

I highly recommend that you install anaconda. All of the packages in the above list come with Anaconda except for networkx. To install networkx go to this link


Here's a list of algorithm implemented in this repo:

Section 1

  • color quantization via k-means and random selection

Section 2

  • minimal spanning tree via my implementation of kruskals algorithm

Section 3

  • Breadth first search algorithm to compute the connected components of a graph.
  • Euclidean Minimum Spanning Tree via my implementation of kruskals algorithm
  • Zahn's Clustering Algorithm
  • ε-neighborhood graph (epsilon neighborhood graph)
  • ε-neighborhood graph clusters

Section 4

  • Mapper Algorithm for dimensionality reduction and analysis.

Section 5

  • Zero Barcode Algorithm for a point cloud
  • Zero Barcode Algorithm for a scalar function

Section 6

  • MDS based node position
  • Laplacian based node position

Section 7

  • MDS for dimensionality reduction
  • ISOMAP for dimensionality reduction
  • PCA for dimensionality reduction

You can read the README files in each section for more details.

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Here are some geometric machine learning algorithms I wrote.

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