composeml.LabelMaker.search

LabelMaker.search(df, num_examples_per_instance, minimum_data=None, gap=None, drop_empty=True, label_type=None, verbose=True, *args, **kwargs)

Searches the data to calculates labels.

Parameters:

• df (DataFrame) – Data frame to search and extract labels.
• num_examples_per_instance (int or dict) – The expected number of examples to return from each entity group. A dictionary can be used to further specify the expected number of examples to return from each label.
• minimum_data (str) – Minimum data before starting search. Default value is first time of index.
• gap (str or int) – Time between examples. Default value is window size. If an integer, search will start on the first event after the minimum data.
• drop_empty (bool) – Whether to drop empty slices. Default value is True.
• label_type (str) – The label type can be “continuous” or “categorical”. Default value is the inferred label type.
• verbose (bool) – Whether to render progress bar. Default value is True.
• *args – Positional arguments for labeling function.
• **kwargs – Keyword arguments for labeling function.

Returns:

Calculated labels with cutoff times.

Return type:

lt (LabelTimes)