MachineLearn: Model module: MachineLearn
In zoonproject/modules: Species Distribution Modelling Code Modules for the ZOON Package

Model module to fit a very large number of machine learning models.

1 2	MachineLearn(.df, method = "glm", tuneLength = 8, metric = "ROC", number = 5, repeats = 1, tuneGrid = NULL, trControl = NULL, ...)

`.df`	Internal parameter, do not use in the workflow function. `.df` is data frame that combines the occurrence
`method`	The machine learning method to use. Common examples are "glm", "nnet", "gbm", "glmnet", "rf". See http://topepo.github.io/caret/modelList.html for a full list. Only classification or dual use models are useable.
`tuneLength`	How many values of each tuning/hyperparameter should be tried?
`metric`	a string that specifies what summary metric will be used to select the optimal model. Options are "ROC", "Accuracy" and "Kappa".
`number`	How many folds to use in cross validation.
`repeats`	How many times should the entire cross validation process be repeated. Increasing this will reduce instability in your model performace, but will take longer to run.
`tuneGrid`	Explicitely pass a data frame of tuning/hyperparameter combinations. If NULL, tuneLength will be used instead.
`trControl`	A named list of further arguments to pass to trainControl. See `trainControl` for details.
`...`	Other arguments passed to `train`.