Machine Learning-Probabilistic Ranking System

Probabilistic Athlete Performance Evaluation & Ranking Software (V2).

Probabilistic models for label ranking

Probabilistic analysis of previous baseball data used to predict outcome of regular season (final team rankings before post-season).

Three coursework pieces: one on Gaussian Processes, another on Probabilistic Ranking, and a final one on Latent Dirichlet Processes

4F13 Probabilistic Ranking Coursework

Imitation learning using probabilistic temporal ranking

Probabilistic Ranking with Gibbs Sampling and Expectation Propagation

POPR-EABC: Probabilistic Offline Policy Ranking with Approximate Bayesian Computation

Probabilistic Reasoning and Bayes Rule; Text Data Analysis; Document Ranking and Evaluation.

Created a document ranking system with Boolean, probabilistic, and vector space models.

An interactive Shiny demo for evaluating Knowledge Graph Embedding models through probabilistic ranking metrics.

Uses Bayesian Networks to prioritize fraud review cases by modeling uncertainty and ranking transactions by probabilistic risk.

This research presents probabilistic machine learning methods to optimize basic image ranking models. And make it suitable for visual navigation and exploration tasks in the real complex world.

An experiment on power analysis in information retrieval. In this notebook, we simulate click models to compare two ranking models (A/B testing) in online environment given offline metrics. Click models implemented: Random Click Model, Position-Based Model. Interleaving methods implemented: Team-Draft, Probabilistic.

An interpreter for a ranked programming language - a variation on probabilistic programming based on Spohn's ranking theory

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This repository is primarily for coursework submission to 4F13: 'Probabilistic machine learning' coursework 2.

Implementation of probabilistic ranking with basic smoothing, and blind relevance feedback

Code to explore learnings in probabilistic ranking methods using match data of top tennis players

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ATP player ranking with Metropolis-Hastings MCMC and Expectation Propagation | Bayesian inference, Python

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Implementing probabilistic ranking with basic smoothing and blind relevance feedback on a subset of TREC ad-hoc track collection

Coursework for 4F13: Probabilistic Machine Learning

Probabilistic rankings of the skills of 2011 ATP men’s tennis players.

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Probabilistic Search Ranking with Python

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Mathematical project exploring search systems and machine learning. Bridged vector space theory with practical ranking algorithms. Tested on Cranfield dataset: achieved 98% dimensionality reduction with 98% ranking performance retained.