I am working with a binary classifier and I want to express the "balance" or "skewness" of the training data using a metric.
I want to reflect this ratio in a report, like this:
Accuracy: 80% Recall: 78% Precision: 62% *The Ratio of Positive to Negative Samples*: 62%
I feel like there's probably a standard name for the metric expressing "The Ratio of Positive to Negative Samples".
My main question is: What is the name of this metric?
(This question assumes that there is a standard name for this metric.)
Here are some example values for the metric and their interpretations:
1.0 = The sample (of training data) is balanced. 0.5 = There are twice as many negative samples as positive samples. 2.0 = There are twice as many positive samples as negative samples.
My secondary question is: Is there another metric that can be used to form similarly meaningful interpretations?