Time Series Ensemble Forecasting

An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model

subsemble R package for ensemble learning on subsets of data

R package - Dynamic Ensembles for Time Series Forecasting

CAVAanalytics is a comprehensive framework for climate data analysis, offering streamlined access to data, advanced processing and visualization capabilities. It is designed to support a wide range of climate research and user needs

Multi-view hierarchical clustering in R

Functional Enrichment Analysis and Network Construction

R package for automatic hyper parameter tuning and ensembles with deep learning, gradient boosting machines, and random forests. Powered by h2o.

autoEnsemble : An AutoML Algorithm for Building Homogeneous and Heterogeneous Stacked Ensemble Models by Searching for Diverse Base-Learners

R Package to process and verify wind forecasts from weather models

This repository contains files and information about step 1 of Kaphta Architecture: Text classification of PubMed abstracts on anticancer activity, using the R language.

Regular S3 model fitting function and methods for EBMAforecast

Snakemake pipeline to reproduce the results in the forthcoming paper "One week ahead prediction of harmful algal blooms in Iowa lakes"

R package for deriving Prediction Rule Ensembles

This repository contains files and information about step 3 of Kaphta Architecture: Indexing of Extracted Information, using the R language.

Ensemble/Blender example in R using Caret (companion code for YouTube video: https://www.youtube.com/watch?v=k7sTiTWWCXM)

Machine Learning competition on Kaggle.org: Random Forest algorithm and ensemble of algorithms to predict Titanic survivors. Top 8% rank

[SIGE-MII-UGR-2016-17] Competición en Kaggle: Titanic

Ensemble

Replication for: Irregular Leadership Changes in 2014: Forecasts using ensemble, split-population duration models, International Journal of Forecasting