sed_eval.sound_event.SegmentBasedMetrics¶
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class
sed_eval.sound_event.SegmentBasedMetrics(event_label_list, time_resolution=1.0)[source]¶ Constructor
Parameters: event_label_list : list, numpy.array
List of unique event labels
time_resolution : float (0,]
Segment size used in the evaluation, in seconds. Default value 1.0
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__init__(event_label_list, time_resolution=1.0)[source]¶ Constructor
Parameters: event_label_list : list, numpy.array
List of unique event labels
time_resolution : float (0,]
Segment size used in the evaluation, in seconds. Default value 1.0
Methods
__init__(event_label_list[, time_resolution])Constructor class_wise_accuracy(event_label[, factor])Class-wise accuracy metrics (sensitivity, specificity, accuracy, and balanced_accuracy) class_wise_count(event_label)Class-wise counts (Nref and Nsys) class_wise_error_rate(event_label)Class-wise error rate metrics (error_rate, deletion_rate, and insertion_rate) class_wise_f_measure(event_label)Class-wise f-measure metrics (f_measure, precision, and recall) evaluate(reference_event_list, ...[, ...])Evaluate file pair (reference and estimated) overall_accuracy([factor])Overall accuracy metrics (sensitivity, specificity, accuracy, and balanced_accuracy) overall_error_rate()Overall error rate metrics (error_rate, substitution_rate, deletion_rate, and insertion_rate) overall_f_measure()Overall f-measure metrics (f_measure, precision, and recall) reset()Reset internal state result_report_class_wise()Report class-wise results result_report_class_wise_average()Report class-wise averages result_report_overall()Report overall results result_report_parameters()Report metric parameters results()All metrics results_class_wise_average_metrics()Class-wise averaged metrics results_class_wise_metrics()Class-wise metrics results_overall_metrics()Overall metrics -