expected_relative_missing_from_table

er_evaluation.expected_relative_missing_from_table(error_table)

Compute expected relative missin elements from record error table.

See er_evaluation.error_analysis.expected_relative_missing().

Parameters:

error_table (DataFrame) – Record error table.

Returns:

Expected relative 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_relative_missing_from_table(error_table)
reference
c1    0.444444
c2    0.500000
c3    0.000000
Name: expected_relative_missing, dtype: float64

The result is the same as calling er_evaluation.error_analysis.expected_relative_missing() directly on prediction and sample:

>>> from er_evaluation.error_analysis import expected_relative_missing
>>> expected_relative_missing(prediction, sample)
reference
c1    0.444444
c2    0.500000
c3    0.000000
Name: expected_relative_missing, dtype: float64