Description Usage Arguments Value
A simple learning and prediction workflow
1 2 | simple_workflow(train, test, form, model = "lm", handleNAs = NULL,
min_train = 2, nORp = 0.2, time = "time", site_id = "site", ...)
|
train |
a data frame for training |
test |
a data frame for testing |
form |
a formula describing the model to learn |
model |
the name of the algorithm to use |
handleNAs |
string indicating how to deal with NAs. If "centralImput", training observations with at least 80% of non-NA columns, will have their NAs substituted by the mean value and testing observatiosn will have their NAs filled in with mean value regardless. |
min_train |
a minimum number of observations that must be
left to train a model. If there are not enough observations,
predictions will be |
nORp |
a maximum number or fraction of columns with missing
values above which a row will be removed from train before
learning the model. Only works if |
time |
the name of the column in |
site_id |
the name of the column in |
... |
other parameters to feed to |
a data frame containing time-stamps, location IDs, true values and predicted values
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