Base.features

property Base.features

An object handling functions manipulating data by features.

A feature is an abstract slice of all data elements of the same kind across different contexts. In a concrete sense, features can be thought of as the data columns but a column can be organized in many ways. To optimize for machine learning, each column should be modified to meet the definition of a feature.

This attribute is an object that can be used to iterate over the features (columns) and contains methods that operate over the data in this object feature-by-feature.

See also

Features, points

Examples

>>> lst = [[1, 2, 3, 4], [5, 6, 7, 8], [0, 0, 0, 0]]
>>> X = nimble.data(lst)
>>> len(X.features)
4
>>> X.features.permute([3, 2, 1, 0])
>>> X
<Matrix 3pt x 4ft
     0  1  2  3
   ┌───────────
 0 │ 4  3  2  1
 1 │ 8  7  6  5
 2 │ 0  0  0  0
>

Keywords: columns, variables, dimensions, attributes, predictors, iterate, items