niftynet.evaluation.classification_evaluations module¶
This module defines built-in evaluation functions for classification applications
Many classification metrics only make sense computed over all subjects, so aggregation is used.
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class
accuracy
(reader, app_param, eval_param)[source]¶ Bases:
niftynet.evaluation.base_evaluations.BaseEvaluation
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layer_op
(subject_id, data)[source]¶ Perform one evaluation calculation for one subject :param subject_id: subject identifier string :param data: a data dictionary as built by ImageReader :return: a list of pandas.DataFrame objects
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get_aggregations
()[source]¶ Returns aggregations to compute for the metric. Each aggregation is a callable that computes a list of DataFrames from a dictionary of metric dataframes (index by the DataFrame index). See BaseEvaluator.ScalarAggregator for an example.
Returns: list of aggregation callables
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