Machine Learning for Emotion Analysis in Python

10

Multiclassifiers

In the preceding chapters, we saw that multi-label datasets, where a tweet may have zero, one, or more labels, are considerably harder to deal with than simple multi-class datasets where each tweet has exactly one label, albeit drawn from a set of more than one option. In this chapter, we will investigate ways of dealing with these cases, looking in particular at the use of neutral as a label for handling cases where a tweet is allowed to have zero labels; at using varying thresholds to enable standard classifiers to return a variable number of labels; and at training multiple classifiers, one per label, and allowing them each to make a decision about the label they were trained for. The conclusion, as ever, will be that ...