Python implementations of clustering algorithms applied on the probability simplex domain (e.g. clustering of softmax predictions from Black-Box source models).

Clustering algorithms implementation

Implementations of decision trees, decision stumps, data visualization and k-nearest neighbours algorithms

An Efficient and Randomized Clustering Algorithm that utilizes Randomized Algorithms on K-Medians

An in-depth exploration of clustering algorithms and techniques in machine learning, with applications focus on Object Tracking and Image Segmentation.

Algorithms related to clustering such as k-Medians, DBSCAN as well as vector quantization.

Testing the effectiveness of Approximate k-NN search with LSH and Hypercube on MNIST. Also, implemented k-medians++ for the same dataset.

This repository is a comprehensive archive of projects and assignments undertaken for the Pattern Recognition course (TIP8311) at the Federal University of Ceará as part of my Master's curriculum.

Comparing different clustering algorithms