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"

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

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

Ensemble

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

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

R package for deriving Prediction Rule Ensembles

This code is part of my Ph.D. research. The objective is to test the best chosen hybrid partitions with silhouette coefficient. It's called HPML Clusters Chains because we chain the labels of each cluster with subsequent clusters. It is a version of HPML where there is only the external chaining.