
test_that("regr_kknn", {
  requirePackagesOrSkip("!kknn", default.method = "load")

  parset.list = list(
    list(),
    list(k = 1),
    list(k = 4),
    list(k = 10)
  )

  old.predicts.list = list()

  for (i in seq_along(parset.list)) {

    parset = parset.list[[i]]
    pars = list(formula = regr.formula, train = regr.train, test = regr.test)
    pars = c(pars, parset)
    m = do.call(kknn::kknn, pars)
    p = predict(m, newdata = regr.test)
    old.predicts.list[[i]] = p
  }

  testSimpleParsets("regr.kknn", regr.df, regr.target, regr.train.inds,
    old.predicts.list, parset.list)

  tt = function(formula, data, k = 7) {
    return(list(formula = formula, data = data, k = k))
  }
  tp = function(model, newdata) {
    kknn::kknn(model$formula, train = model$data, test = newdata,
      k = model$k)$fitted
  }

  testCVParsets("regr.kknn", regr.df, regr.target, tune.train = tt,
    tune.predict = tp, parset.list = parset.list)
})
