nltk.chunk.ChunkScore¶

class nltk.chunk.ChunkScore(**kwargs)[source]¶

A utility class for scoring chunk parsers. ChunkScore can evaluate a chunk parser’s output, based on a number of statistics (precision, recall, f-measure, misssed chunks, incorrect chunks). It can also combine the scores from the parsing of multiple texts; this makes it significantly easier to evaluate a chunk parser that operates one sentence at a time.

Texts are evaluated with the score method. The results of evaluation can be accessed via a number of accessor methods, such as precision and f_measure. A typical use of the ChunkScore class is:

>>> chunkscore = ChunkScore()           
>>> for correct in correct_sentences:   
...     guess = chunkparser.parse(correct.leaves())   
...     chunkscore.score(correct, guess)              
>>> print('F Measure:', chunkscore.f_measure())       
F Measure: 0.823

Variables:

kwargs – Keyword arguments: max_tp_examples: The maximum number actual examples of true positives to record. This affects the correct member function: correct will not return more than this number of true positive examples. This does not affect any of the numerical metrics (precision, recall, or f-measure) max_fp_examples: The maximum number actual examples of false positives to record. This affects the incorrect member function and the guessed member function: incorrect will not return more than this number of examples, and guessed will not return more than this number of true positive examples. This does not affect any of the numerical metrics (precision, recall, or f-measure) max_fn_examples: The maximum number actual examples of false negatives to record. This affects the missed member function and the correct member function: missed will not return more than this number of examples, and correct will not return more than this number of true negative examples. This does not affect any of the numerical metrics (precision, recall, or f-measure) chunk_label: A regular expression indicating which chunks should be compared. Defaults to '.*' (i.e., all chunks). _tp – List of true positives _fp – List of false positives _fn – List of false negatives _tp_num – Number of true positives _fp_num – Number of false positives _fn_num – Number of false negatives.