Mind Foundry OPTaaS R Client
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Updated
Nov 30, 2018 - R
Mind Foundry OPTaaS R Client
An R Package to return a variety of different model types, complete with hyper-parameter tuning
Predicting the Surge Pricing Type for Sigma Cabs
Machine learning models build on real time data
Machine Learning Hyper-parameter Tuning processes
This repository contains Prior-RObust Bayesian Optimization (PROBO) as introduced in our paper "Accounting for Gaussian Process Imprecision in Bayesian Optimization"
R, Data Mining, Hyperparameter Tuning
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.
An example of how to use irace with Julia on a Windows computer
Instructional materials (course files) for the BBT4206 course (Business Intelligence II) using R. Topic: Hyperparameter Tuning.
An R-toolkit for model evaluation, model comparison and hyperparameter tuning based on cross-validation
Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models
Performs Variables selection and model tuning for Species Distribution Models (SDMs). It provides also several utilities to display results.
R interface to Keras Tuner
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.
An extensible framework for reproducible machine learning experiments
Successive Halving and Hyperband in the mlr3 ecosystem
Black-box optimization framework for R.
Collection of search spaces for hyperparameter optimization in the mlr3 ecosystem
Hyperparameter optimization package of the mlr3 ecosystem
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