development

Machine Learning Algorithms with Unified Interface and Confusion Matrices

Asymptotic Efficient Closed-Form Estimators for Multivariate Distributions

Computation of the MLE for Bivariate Interval Censored Data

Maximum Likelihood Estimates of Gaussian Processes

MLE for Normally Distributed Data Censored by Limit of Detection

Multilevel Exponential-Family Random Graph Models

Machine Learning Model Evaluation

Machine Learning Experiments

Machine Learning Foundations

High Dimensional Mediation Analysis using Local False Discovery Rates

Iterative Proportional Fitting Algorithms for Nested Structures

Interface to 'MLflow'

Machine Learning Forest Simulator

Datasets for Use with Salvan, Sartori and Pace (2020)

Multi-Layer Group-Lasso

Multilevel Index of Dissimilarity

Single and Multiple Imputation with Automated Machine Learning

Cell Type Annotation Using Large Language Models

R6-Based ML Learners for 'mlexperiments'

Multilevel Mediation Analysis

Multi-Level Monte Carlo

Machine Learning Evaluation Metrics

Multilevel/Mixed Model Helper Functions

Maximum Likelihood Multiple Imputation

Maximum Likelihood Estimation of DNA Methylation and Hydroxymethylation Proportions

Maximum Likelihood Models and Tools for Estimation, Prediction, and Testing

Model Selection in Multivariate Longitudinal Data Analysis

Probing, Plotting, and Interpreting Multilevel Interaction Effects

Estimating Frequencies, Prevalence and Multiplicity of Infection

Integrating Morphological Modeling and Machine Learning for Decision Support

Power Analysis and Data Simulation for Multilevel Models

Examples from Multilevel Modelling Software Review

Multilevel Monitoring System Data for Wells in the USGS INL Aquifer Monitoring Network

Multi-Level Model Assessment Kit

Machine Learning Algorithms for Multivariate Time Series

Practical Multilevel Modeling

Multinomial Logit Models

Bayesian Model Averaging for Multinomial Logit Models

'Rcpp' Integration for the 'mlpack' Library

Maximum Likelihood Estimation of the Niche Preemption Model

Multi-Label Prediction Using Gibbs Sampling (and Classifier Chains)

A Power Analysis Toolbox to Find Cost-Efficient Study Designs

Algorithms for Class Distribution Estimation

Machine Learning in R

Batch Experiments for 'mlr3'

Analysis and Visualisation of Benchmark Experiments

Collection of Machine Learning Data Sets for 'mlr3'

Data Base Backend for 'mlr3'

Fairness Auditing and Debiasing for 'mlr3'

Filter Based Feature Selection for 'mlr3'

Feature Selection for 'mlr3'

Hyperband for 'mlr3'

Inference on the Generalization Error

Flexible Bayesian Optimization

Performance Measures for 'mlr3'

Connector Between 'mlr3' and 'OpenML'

Preprocessing Operators and Pipelines for 'mlr3'

Resampling Algorithms for 'mlr3' Framework

Machine Learning in 'shiny' with 'mlr3'

Support for Spatial Objects Within the 'mlr3' Ecosystem

Spatiotemporal Resampling Methods for 'mlr3'

Model and Learner Summaries for 'mlr3'

Super Learner Fitting and Prediction

Deep Learning with 'mlr3'

Hyperparameter Optimization for 'mlr3'

Search Spaces for 'mlr3'

Easily Install and Load the 'mlr3' Package Family

Visualizations for 'mlr3'

Composable Preprocessing Operators and Pipelines for Machine Learning

Model-Based Optimization for 'mlr3' Through 'mlrMBO'

Bayesian Optimization and Model-Based Optimization of Expensive Black-Box Functions

Stepwise Regression with Assumptions Checking

Long-Run Variance Estimation in Time Series Regression

Unified S3 Interface to Machine Learning Models

Efficient Estimation of Bayesian SBMs & MLSBMs

Use the MLS Junk Generator Algorithm to Generate a Stream of Pseudo-Random Numbers

Machine Learning Models for Soil Properties

Machine Learning and Mapping for Spatial Epidemiology

Multilevel Supervised Topic Models with Multiple Outcomes

Support Compatibility Between 'Maelstrom' R Packages and 'Opal' Environment

R6-Based ML Survival Learners for 'mlexperiments'