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.

Methods

There are 2 methods for FastTabular.TabularRegression: