update and lint docstring
@@ -1405,20 +1405,22 @@ class Linker:
return profile_columns(self, column_expressions, top_n=top_n, bottom_n=bottom_n)
def estimate_m_from_pairwise_labels(self, table_name):
- """Estimate the m parameters of the linkage model from a dataframe of pairwise labels.
+ """Estimate the m parameters of the linkage model from a dataframe of pairwise
+ labels.
The table of labels should be in the following format, and should
be registered with your database:
- |source_dataset_l|unique_id_l|source_dataset_r|unique_id_r|clerical_match_score|
- |----------------|-----------|----------------|-----------|--------------------|
- |df_1 |1 |df_2 |2 |0.99 |
- |df_1 |1 |df_2 |3 |0.2 |
+ |source_dataset_l|unique_id_l|source_dataset_r|unique_id_r|
+ |----------------|-----------|----------------|-----------|
+ |df_1 |1 |df_2 |2 |
+ |df_1 |1 |df_2 |3 |
Note that `source_dataset` and `unique_id` should correspond to the
values specified in the settings dict, and the `input_table_aliases`
- passed to the `linker` object. Note that at the moment
- `clerical_match_score` is ignored and it is assumed that every row in
- the table of labels is a score of 1, i.e. a perfect match.
+ passed to the `linker` object. Note that at the moment, this method does
+ not respect values in a `clerical_match_score` column. If provided, these
+ are ignored and it is assumed that every row in the table of labels is a score
+ of 1, i.e. a perfect match.
Args:
labels_tablename (str): Name of table containing labels in the database
