Connection
Base URL, credentials and a reachable server.
Product
Product features · Machine-learning data splits
01
Split machine-learning data by the entity that could leak across sets. Keep each group on one side and fit preprocessing on training data before applying it to held-out rows.
Selection
A model available through the configured endpoint.
Capabilities
Context limits and tool support are determined by the model and server.
Machine-learning data splits
● ● ●Model Ledger●
A concrete starting point · Machine-learning data splits ×
train_groups, test_groups = split_groups(group_ids)
assert not set(train_groups) & set(test_groups)
train = rows_in_groups(data, train_groups)
test = rows_in_groups(data, test_groups)✳Split machine-learning data by the entity that could leak across sets.
✓ ChangesReview before applying ↗
Illustrative workspace