July 2017
Beginner to intermediate
715 pages
17h 3m
English
As we have already discussed, the binary classification model deals with the case when there are only two possible outcomes that we want to predict. Typically, in these settings, we have items of the positive class (the presence of some effect) and items of the negative class (the absence of some effect).
For example, the positive label can be relevant, duplicate, fail to pay the debts, and so on. The instances of the positive class are typically assigned the target value of 1. Also, we have negative instances, such as not relevant, not duplicate, pays the debts, and they are assigned the target value of 0.
This separation into positive and negative classes is somewhat artificial, and in some cases does not ...