An RShiny dashboard for visualisation of mass spectrometry (MS) data and fine-tuning of xcms pre-processing parameters

The iraceplot package allows to plot configuration data obtained by configuration process performed by the irace configurator.

Resample, parameter tuning, meta-learning, clustering, and mining algorithms for the purpose of data mining and machine learning.

We compared the predictive accuracy and sparsity of support vector machines and relevance vector machines for a range of synthetic data sets differing in signal-to-noise ratio and other measures of difficulty.

This is a solution to a Kaggle competition on predicting claim severity for Allstate Insurance using the Extreme Gradient Boosting (XgBoost) algorithm in R

Using machine learning techniques with Kepler Space Telescope exoplanet search data to train and tune classification models