Subkey

Description

Use

Percentage of times Object (e.g. patient) resampling is used.

Method

One of the methods adopted, see also imbalanced learn <https://imbalanced-learn.readthedocs.io/en/stable/api/>`_.

sampling_strategy

Sampling strategy, see also imbalanced learn <https://imbalanced-learn.readthedocs.io/en/stable/api/>`_.

n_neighbors

Number of n_neighbors used in resampling. This should be (much) smaller than the number of objects/patients you supply. We sample on a uniform scale: the parameters specify the range (loc, loc + scale).

k_neighbors

Number of n_neighbors used in resampling. This should be (much) smaller than the number of objects/patients you supply. We sample on a uniform scale: the parameters specify the range (loc, loc + scale).

threshold_cleaning

Threshold for cleaning of samples. We sample on a uniform scale: the parameters specify the range (loc, loc + scale).