Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data

k-modes and k-prototypes clustering algorithms implementation in Go

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Customer segmentation using k-modes unsupervised clustering

Code for our IEEE TPAMI 2024 paper "Simplex Clustering via sBeta With Applications to Online Adjustment of Black-Box Predictions" - Python implementation of clustering algorithms applied on the probability simplex domain (e.g. clustering of softmax predictions from Black-Box source models).

Classifying bank transactions with unsupervised k-prototypes clustering.

Repository for "Data Mining - Advanced Topics and Applications" projects exam.

Swarm based clustering and K-Means

Species identification based on mass spectrometry biomarker clustering

k-prototypes for numerical and categorical clustering

This project compares the efficiency and accuracy of different machine learning models on 3 unrelated datasets but having the same theme i.e. car data.

Using data science and analysis to gain insight on demographic distribution, identify clusters in which various platforms lie, and building predictive models to predict the probability of a user using a particular application.

Bachelor thesis is submitted in fulfilment of the requirements for the Bachelor of Science degree in the Department of Business Analytics and Information Technologies at the Faculty of Applied Sciences of Ukrainian Catholic University.