The description is extended.
A {pkgdown} site is added.
mlKnn() is implemented for K-nearest neigbours.
Several adjustments were required for compatibility with R 4.2.0 (it is not allowed any more to use vectors > 1 with || and &&).
predict() was applied to an mlearning object build with full formula (not the short one var ~ .), if the dependent variable was not in newdata =, an error message was raised (although this variable is not necessary at this point). Bug identified by Damien Dumont, and corrected.mlSvm.formula(), arguments scale=, type=, kernel= and classwt= were not correctly used. Corrected.mlLvq() providing size = or prior = led to an lvq object not found message. Corrected.Sometines, data was not found (e.g., when called inside a learnr).
In mlearning(), data is forced with as.data.frame() (tibbles are not supported internally).
In the mlXXX() function, it was not possible to indicate something like mlLda(data = iris, Species ~ .). Solved by adding train = argument in mlXXX().
In summary.confusion() produced an error if more than one type = was provided.