R: Multi-Response (Multivariate) Interpretable Machine Learning

# Multi-Response (Multivariate) Interpretable Machine Learning

## Documentation for package ‘mrIML’ version 2.2.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

cbind | A cbind variation that ignores objects with zero dimention
filterRareCommon | Filter rare response variables from the data
mrBootstrap | Bootstrap mrIML model predictions
mrCoOccurNet | Generate a MrIML co-occurrence network
mrCovar | Investigate partial dependencies of a covariate for mrIML JSDMs (Joint Species Distribution Models)
mrFlashlight | Convert mrIML object into a 'flashlight' object
mrIMLperformance | Calculate general performance metrics of a mrIML model
mrIMLpredicts | Generates a multi-response predictive model
mrIML_bird_parasites_LM | An example mrIML model fit to MRFcov::Bird.parasites
mrIML_bird_parasites_RF | An example mrIML model fit to MRFcov::Bird.parasites
mrInteractions | Calculate and visualize feature interactions
mrPdPlotBootstrap | Bootstrap Partial Dependence Plots
mrPerformancePlot | Plot Model Performance Comparison
mrShapely | Generate SHAP (SHapley Additive exPlanations) Plots for Multiple Models and Responses
mrVip | Calculates and helps interpret variable importance for 'mrIML' models.
mrVipPCA | Principal Component Analysis of mrIML variable importance
readSnpsPed | Conversion to single column per locus from plink file via LEA functionality
resist_components | Calculates resistance components from a list of pairwise resistance surfaces