- Y
Outcome variable
- X
Training dataframe
- newX
Test dataframe
- family
Gaussian or binomial
- k
Number of nearest neighbors to use
- method
Distance method, can be 'euclidean' (default), 'manhattan',
'chebyshev', 'canberra', 'braycurtis', 'pearson_correlation',
'simple_matching_coefficient', 'minkowski' (by default the order 'p' of the
minkowski parameter equals k), 'hamming', 'mahalanobis',
'jaccard_coefficient', 'Rao_coefficient'
- weights_function
Weighting method for combining the nearest neighbors.
Can be 'uniform' (default), 'triangular', 'epanechnikov', 'biweight',
'triweight', 'tricube', 'gaussian', 'cosine', 'logistic', 'gaussianSimple',
'silverman', 'inverse', 'exponential'.
- extrema
if TRUE then the minimum and maximum values from the
k-nearest-neighbors will be removed (can be thought as outlier removal).
- h
the bandwidth, applicable if the weights_function is not NULL.
Defaults to 1.0.
- ...
Any additional parameters, not currently passed through.