Random Forest: "rf". Regression and classification.
Implemented via ranger
.
mtry: Fraction of variables to consider for each split
splitrule: Splitting rule. For classification either "gini" or "extratrees". For regression either "variance", "extratrees", or "maxstat".
min.node.size: Minimal node size.
k-nearest neighbors: "knn". Regression and classification.
Implemented via kknn
.
kmax: Number of neighbors to consider.
distance: Minkowsky distance parameter, (0, Inf). 1 = Manhatten, 2 = Euclidian, -> Inf = Chebyshev.
kernal: Kernal to use. Possible choices are "rectangular" (standard knn), "triangular", "epanechnikov", "biweight", "triweight", "cos", "inv", "gaussian", "rank", or "optimal".
get_supported_models()
Vector of currently-supported algorithms.
hyperparameters
for more detail on hyperparameter
defaults and specifications