A Cython Machine Learning library dedicated to Hidden Markov Models
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Updated
Aug 1, 2023 - Python
A Cython Machine Learning library dedicated to Hidden Markov Models
Implemented Gaussian Mixture Models (GMM) for image color segmentation.
A machine learning clustering model for customer segmentation to define marketing strategy.
Infinite Mixtures of Infinite Factor Analysers
Suite for human/nonhuman binary classification problem using MOG, CNN with VIRAT2.0-based dataset
Coordinate ascent mean-field variational inference (CAVI) using the evidence lower bound (ELBO) to iteratively perform the optimal variational factor distribution parameter updates for clustering.
Code and data for "Superclass-class conditional Gaussian mixture model for learning fine-grained embeddings" @ ICLR2022
Differential Evolution Clustering
This repository contains functions/codes related to different methods of machine learning for classification and clustering in python.
Synthetic Data Generation (SDG) by Gaussian Mixture Model (GMM) Distribution
Library and hand-made clustering algorithms are implemented in this project
Codes for simulation studies to examine the performance of the EM algorithm and its modifications Classification EM and Stochastic EM for Gaussian mixture and a mixture of Markov chains.
Privacy-Preserving Distributed Expectation Maximization for Gaussian Mixture Models via Fully Homomorphic Encryption
Algorithms proposed in the following paper: G. Oliveira, L. L. Minku and A. L. I. Oliveira, "Tackling Virtual and Real Concept Drifts: An Adaptive Gaussian Mixture Model Approach," in IEEE Transactions on Knowledge and Data Engineering, 2021. doi: 10.1109/TKDE.2021.3099690.
Machine Learning Engineer Nanodegree, Unsupervised Learning, Creating Customer Segments
Detecting stock market phases using a Gaussian mixture model.
Fast explication of Gaussian Mixture model for clustering
Image classification of Iris Flower dataset using 5 different machine learning methods (Decision Tree, Support Vector Machine, Random Forest, Naive Bayes and K-nearest neighbour)
Implementation of EM algorithm for the Gaussian mixture model.
Data Science Project (Autonomous Driving Dataset Analysis)
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