Mutual Information-based Non-linear Clustering Analysis
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Updated
Jun 26, 2024 - Python
Mutual Information-based Non-linear Clustering Analysis
A concatenation of two GNNs to decode dynamic clustering on localization datasets
A Comparative report between Clustering-Based Anomaly Detection & K-means Clustering
Project to demonstrate various clustering algorithms for customer segmentation.
Comparative clustering and visualization of socioeconomic and health indicators: A case of 47 counties in Kenya.
scRNA-Explorer pipeline allows users to interrogate in an interactive manner scRNA-sequencing data sets to explore via gene expression correlations possible function(s) of a gene of interest
The model predicts the treatment success rate for new TB cases with high accuracy and robustness. Two different approaches: PCA and Bayesian Inference. The Bayesian regression analysis reveals that c_new_sp_tsr and new_sp_fail are significant predictors of the treatment success rate, while other predictors show less certainty in their effects.
Expectation-Maximization-based clustering algorithm to identify groups defined by biological variates as clusters in single-cell transcriptomic data.
A comprehensive bundle of utilities for the estimation of probability of informed trading models: original PIN in Easley and O'Hara (1992) and Easley et al. (1996); Multilayer PIN (MPIN) in Ersan (2016); Adjusted PIN (AdjPIN) in Duarte and Young (2009); and volume-synchronized PIN (VPIN) in Easley et al. (2011, 2012). Implementations of various …
Phenomenological power spectrum models for Halpha emission line galaxies from the Nancy Grace Roman Space Telescope (2023MNRAS.523.2498M)
Clustering - Cohort Analysis - Retention Analysis
Spatial Analysis of Crime and SES in Washington D.C. Completed in fulfillment of GG4257: Urban Analytics as a Toolkit for Sustainable Development.
Analyzing and recommending Amazon products using graph-based methods and regression models.
Docker powered starter for geospatial analysis of lightning atmospheric data.
This repository contains an ML project that was approached with a business mindset from the beginning to the end. It addresses the problem of clustering.
Predictive Modeling and Clustering Insights for Kickstarter Success
Clustering and resource allocation using Deterministic Annealing Approach and Orthogonal Non-negative Matrix Factorization O-(NMF)
My projects for the Practical Data Science course in the MSc in Data Science, AUEB.
This project implements cohort, RFM and Clustering based analyses to identify various customer segments of a retail business for developing group specific marketing strategies based on customer purchasing behaviours.
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