1 citations · 1 across the 3 of their papers we have counts for
3 papers
Bayesian Decision Trees Inspired from Evolutionary Algorithms
Efthyvoulos Drousiotis, Alexander M. Phillips, Paul G. Spirakis +1
Bayesian Decision Trees (DTs) are generally considered a more advanced and accurate model than a regular Decision Tree (DT) because they can handle complex and uncertain data. Exis…
Parallel Approaches to Accelerate Bayesian Decision Trees
Efthyvoulos Drousiotis, Paul G. Spirakis, Simon Maskell
Markov Chain Monte Carlo (MCMC) is a well-established family of algorithms primarily used in Bayesian statistics to sample from a target distribution when direct sampling is challe…
Single MCMC Chain Parallelisation on Decision Trees
Efthyvoulos Drousiotis, Paul G. Spirakis
Decision trees are highly famous in machine learning and usually acquire state-of-the-art performance. Despite that, well-known variants like CART, ID3, random forest, and boosted…