bilbo package

Subpackages

• bilbo.components package
  • Subpackages
    • bilbo.components.crf package
      • Submodules
      • bilbo.components.crf.crf module
      • Module contents
    • bilbo.components.features package
      • Submodules
      • bilbo.components.features.decorator_feature module
      • bilbo.components.features.externalfeatures module
      • bilbo.components.features.features module
      • bilbo.components.features.localfeatures module
      • bilbo.components.features.regexfeatures module
      • bilbo.components.features.xmlfeatures module
      • Module contents
    • bilbo.components.shape_data package
      • Submodules
      • bilbo.components.shape_data.shape_data module
      • Module contents
    • bilbo.components.svm package
      • Submodules
      • bilbo.components.svm.svm module
      • Module contents
  • Submodules
  • bilbo.components.component module
  • Module contents
• bilbo.libs package
  • Submodules
  • bilbo.libs.opts module
  • Module contents
• bilbo.storage package
  • Submodules
  • bilbo.storage.document module
  • bilbo.storage.section module
  • bilbo.storage.token module
  • bilbo.storage.trie module
  • Module contents
• bilbo.tests package
  • Submodules
  • bilbo.tests.test_feature module
  • bilbo.tests.test_importer module
  • bilbo.tests.test_shapesection module
  • bilbo.tests.tests module
  • Module contents
• bilbo.tokenizers package
  • Submodules
  • bilbo.tokenizers.en module
  • bilbo.tokenizers.fr module
  • bilbo.tokenizers.tokenizers module
  • Module contents
• bilbo.utils package
  • Submodules
  • bilbo.utils.crf_datas module
  • bilbo.utils.dictionaries module
  • bilbo.utils.svm_datas module
  • bilbo.utils.timer module
  • Module contents

Submodules

bilbo.bilbo module

bilbo.eval module

class bilbo.eval.Evaluation(gold, predicted, option='fine')

Bases: object

Evaluation class

evaluate()

Compute all the precisions, recalls, f-measures and count for the confusion matrix :return: dict(label, precision), dict(label, recall), dict(label, f_measures), dict(label, count), dict(macro)

get_col_sum(label)

return the sum of a given column

get_confusion_matrix()

Generate the confusion matrix populate matrix with the confusion matrix populate imap

get_count_for_label(label)

param label : a given label return the number of occurences for a given label

get_count_for_labels()

return a dict with the number of occurences for each label :return: dict (label, count)

get_f_measure_for_labels(beta: float = 1)

Returns F1 score for all labels. See http://en.wikipedia.org/wiki/F1_score

Parameters:beta –

the beta parameter higher than 1 prefers recall,

lower than 1 prefers precision

Returns:dict (label, F1)

get_macro_f_measure()

Returns:the mean f-measure for the whole document

get_macro_f_measure_weighted()

Returns:the weighted mean f-measure for the whole document

get_macro_precision()

get_macro_precision_weighted()

get_macro_recall()

get_macro_recall_weighted()

get_precision_for_label(label)

param label : a given label return the precision for a given label

get_precision_for_labels()

return a dict with the precition of each label :return: dict (label, precision)

get_recall_for_label(label)

param label : a given label return the recall for a given label

get_recall_for_labels()

return a dict with the recall of each label :return: dict (label, recall)

get_row_sum(label)

return the sum of a given row

get_true_positive(label)

return the true positive from the matrix

get_unique_label()

return a list of unique label from the gold and predicted lists

print_csv(precisions, recalls, f_measures, counts, macro, csvfile)

print_std(precisions, recalls, f_measures, counts, macro)

bilbo.generateXml module

bilbo.importer module

Module contents