Thresholding classifiers
Logistic regression classifiers are often deployed with a threshold rather than the provided classifier.bestCategory() method. This method picks the category with the highest conditional probability, which, in a 3-way classifier, can be just above one-third. This recipe will show you how to adjust classifier performance by explicitly controlling how the best category is determined.
This recipe will consider the 3-way case with the p, n, and o labels and work with the classifier produced by the Classifier-building life cycle recipe earlier in this chapter. The cross-validation evaluation produced is:
Category p Recall: 0.64 Prec : 0.57 Category n Recall: 0.41 Prec : 0.54 Category o Recall: 0.81 Prec : 0.81
We will run novel data to set thresholds.
How to do it...
Our business use case is that recall be maximized while p has .65 precision and n has .5 precision for reasons discussed in the Classifier-building life cycle recipe. The o category is not important in this...
