lenskit.splitting.split_global_time#

lenskit.splitting.split_global_time(data: Dataset, time: int | float | str | datetime, end: int | float | str | datetime | None = None) → TTSplit#

lenskit.splitting.split_global_time(data: Dataset, time: Sequence[int | float | str | datetime], end: int | float | str | datetime | None = None) → list[TTSplit]

Global temporal train-test split. This splits a data set into train/test pairs using a single global timestamp. When given multiple timestamps, it will return multiple splits, where split $i$ has training data from before $t_i$ and testing data on or after $t_i$ and before $t_{i+1}$ (the last split has no upper bound on the testing data).

Stability:

Caller (see Stability Levels).

Parameters:

• data – The dataset to split.

• time – Time or sequence of times at which to split. Strings must be in ISO format.

• end – A final cutoff time for the testing data.

Returns:

The data splits.