poetryFNs.append(poetryFN) fictionTPs.append(fictionTP) fictionFPs.append(fictionFP) fictionTNs.append(fictionTN) fictionFNs.append(fictionFN) dramaTPs.append(dramaTP) dramaFPs.append(dramaFP) dramaTNs.append(dramaTN) dramaFNs.append(dramaFN) for genre in genrestocheck: precision = predicted.genreaccuracy(genre, correctgenres) if precision <= 1: utils.appendtodict(genre, predicted.genrefeatures(genre), genrefeatures) utils.appendtodict(genre, precision, genreprecisions) utils.appendtodict(genre, True, modeledvols) else: utils.appendtodict(genre, False, modeledvols) # Precision > 1 is a signal that we actually have no true or false # positives in the volume for this genre. In that circumstance, we're # not going to use the volume to train a metamodel for the genre, because # it won't usefully guide what we want to guide -- assessment of the # accuracy of our positive predictions for this genre. # # So we don't append the genre features or precision to the arrays # that are going to be used to create a genre-specific metamodel. # # On the other hand, there could be false negatives in the volume, and # we want to acknowledge that when calculating overall recall.
poetryFNs.append(poetryFN) fictionTPs.append(fictionTP) fictionFPs.append(fictionFP) fictionTNs.append(fictionTN) fictionFNs.append(fictionFN) dramaTPs.append(dramaTP) dramaFPs.append(dramaFP) dramaTNs.append(dramaTN) dramaFNs.append(dramaFN) for genre in genrestocheck: precision = predicted.genreaccuracy(genre, correctgenres) if precision <= 1: utils.appendtodict(genre, predicted.genrefeatures(genre), genrefeatures) utils.appendtodict(genre, precision, genreprecisions) utils.appendtodict(genre, True, modeledvols) else: utils.appendtodict(genre, False, modeledvols) # Precision > 1 is a signal that we actually have no true or false # positives in the volume for this genre. In that circumstance, we're # not going to use the volume to train a metamodel for the genre, because # it won't usefully guide what we want to guide -- assessment of the # accuracy of our positive predictions for this genre. # # So we don't append the genre features or precision to the arrays # that are going to be used to create a genre-specific metamodel. # # On the other hand, there could be false negatives in the volume, and # we want to acknowledge that when calculating overall recall.