jackknife Interface

Jackknifing is a procedure used to create “un-biased” predictions from a training set. It employs a system similar to K-fold Cross Validation where the dataset is divided into K different slices. Then, a model is trained for each combination of K-1 slices and creates predictions for the remaining slice. This is a lengthy process as it requires K training runs of the model.

Note: Args that start with ‘--’ (eg. --save-config) can also be set in a config file (specified via --config). The config file uses YAML syntax and must represent a YAML ‘mapping’ (for details, see http://learn.getgrav.org/advanced/yaml). If an arg is specified in more than one place, then command line values override config file values which override defaults.

For generic options see: here

usage: kiwi jackknife [-h] [--splits SPLITS] [--train-config TRAIN_CONFIG]

jackknifing

--splits	Jackknife with X folds. Default: 5
--train-config	Path to config file with model parameters.