expected_missing_from_table#
- er_evaluation.expected_missing_from_table(error_table)[source]#
Compute expected missin elements from record error table.
See
er_evaluation.error_analysis.expected_missing().- Parameters:
error_table (DataFrame) – Record error table.
- Returns:
Expected missin elements 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_missing_from_table(error_table) reference c1 1.333333 c2 1.000000 c3 0.000000 Name: expected_missing, dtype: float64
The result is the same as calling
er_evaluation.error_analysis.expected_missing()directly onpredictionandsample:>>> from er_evaluation.error_analysis import expected_missing >>> expected_missing(prediction, sample) reference c1 1.333333 c2 1.000000 c3 0.000000 Name: expected_missing, dtype: float64