expected_size_difference_from_table#
- er_evaluation.expected_size_difference_from_table(error_table)[source]#
Compute expected size difference from record error table.
See
er_evaluation.error_analysis.expected_size_difference().- Parameters:
error_table (DataFrame) – Record error table.
- Returns:
Expected size difference for each reference cluster.
- Return type:
Series
Examples
>>> prediction = pd.Series(index=[1,2,3,4,5,6,7,8], data=[1,1,2,3,2,4,4,4]) >>> sample = pd.Series(index=[1,2,3,4,5,6,7], data=["c1", "c1", "c1", "c2", "c2", "c3", "c3"]) >>> error_table = record_error_table(prediction, sample) >>> expected_size_difference_from_table(error_table) reference c1 -1.0 c2 -0.5 c3 1.0 Name: expected_size_diff, dtype: float64
The result is the same as calling
er_evaluation.error_analysis.expected_size_difference()on prediction and sample:>>> from er_evaluation.error_analysis import expected_size_difference >>> expected_size_difference(prediction, sample) reference c1 -1.0 c2 -0.5 c3 1.0 Name: expected_size_diff, dtype: float64