Statistics - (Threshold|Cut-off) of binary classification

1 - About

The Threshold or Cut-off represents in a binary classification the probability that the prediction is true.

It represents the tradeoff between false positives and false negatives.

3 - Example

Normally, the cut-off will be on 0.5 (random) but you can increase it to for instance 0.6. All predicted outcome with a probability above it will be classified in the first class and the other in the other class.

data_mining/threshold.txt · Last modified: 2015/04/13 11:16 by gerardnico