Beast code in Giters

Johannes Haupt's repositories

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Exercises on Bayesian methods for machine learning

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Experiments showing the profit efficiency of targeted randomized sampling in comparison to standard A/B testing

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Code accompanying the paper "Customer targeting under response-dependent costs"

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Calculate mean decrease in entropy as a variable importance metric for C5.0 boosted trees in R

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Particle swarm optimization (PSO) that supports constraints

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Python package for the deep distribution regression method.

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A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

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Pytorch implementation of Wasserstein GANs with Gradient Penalty

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R and python implementations of Accelerated Bayesian Causal Forest.

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