Iterated Racing for Automatic Algorithm Configuration
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Updated
Aug 30, 2024 - R
Iterated Racing for Automatic Algorithm Configuration
Black-box optimization framework for R.
Performs Variables selection and model tuning for Species Distribution Models (SDMs). It provides also several utilities to display results.
R interface to Keras Tuner
Hyperparameter optimization package of the mlr3 ecosystem
Successive Halving and Hyperband in the mlr3 ecosystem
Collection of search spaces for hyperparameter optimization in the mlr3 ecosystem
An extensible framework for reproducible machine learning experiments
Flexible Bayesian Optimization in R
An R-toolkit for model evaluation, model comparison and hyperparameter tuning based on cross-validation
Data mining and machine learning libraries are used in this machine learning project to detect the fraud. More importantly, this report focuses on vehicle insurance company claim statistics to use the gathered knowledge from actuarial Science Course.
This R-based data science project on the UCI Parkinson's dataset employs machine learning (Decision tree, Random Forest, SVM, XGBoost) with a focus on hyperparameter tuning and feature selection. This repository showcases insights into Parkinson's disease prediction using effective data science practices.
Machine learning models build on real time data
R, Data Mining, Hyperparameter Tuning
Instructional materials (course files) for the BBT4206 course (Business Intelligence II) using R. Topic: Hyperparameter Tuning.
An R Package to return a variety of different model types, complete with hyper-parameter tuning
Mind Foundry OPTaaS R Client
Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models
Predicting the Surge Pricing Type for Sigma Cabs
This repository contains Prior-RObust Bayesian Optimization (PROBO) as introduced in our paper "Accounting for Gaussian Process Imprecision in Bayesian Optimization"
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