TabularRegression
function
defined in module
FastTabular
TabularRegression(blocks, data)
Learning task for tabular regression. Continuous columns are normalized and missing values are filled, categorical columns are label encoded taking into account any missing values which might be present.
blocks
should be an input and target block
(TableRow(...), Continuous(...))
.
TabularRegression(n, tabledata [; catcols, contcols])
Construct learning task with
classes
to classify into and a
TableDataset
tabledata
. The column names can be passed in or guessed from the data. The regression target is a vector of
n
values.
There are
2
methods for FastTabular.TabularRegression
:
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