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test_that("classif_knn", {
requirePackagesOrSkip("class", default.method = "load")
parset.list = list(
list(),
list(k = 10)
)
old.predicts.list = list()
old.probs.list = list()
for (i in seq_along(parset.list)) {
parset = parset.list[[i]]
train = multiclass.train
y = train[, multiclass.target]
train[, multiclass.target] = NULL
test = multiclass.test
test[, multiclass.target] = NULL
pars = list(train = train, cl = y, test = test)
pars = c(pars, parset)
p = do.call(class::knn, pars)
old.predicts.list[[i]] = p
}
testSimpleParsets("classif.knn", multiclass.df, multiclass.target, multiclass.train.inds,
old.predicts.list, parset.list)
tt = function(formula, data, k = 1) {
return(list(formula = formula, data = data, k = k))
}
tp = function(model, newdata) {
target = as.character(model$formula)[2]
train = model$data
y = train[, target]
train[, target] = NULL
newdata[, target] = NULL
class::knn(train = train, cl = y, test = newdata, k = model$k)
}
testCVParsets("classif.knn", multiclass.df, multiclass.target, tune.train = tt,
tune.predict = tp, parset.list = parset.list)
})
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