So I'm just starting to learn some proper statistics and recently learned about FP, FN, TP, TN.
I'm a little confused as to how that works.
Firstly lets say I have a way to predict whether a variable X is either 1 or 0 considering 1 to be positive and 0 to be negative. The quirk is that it is only correct some of the time
So lets say I have these values
The model is correct 40% of the time
The model is wrong 60% of the time
It predicts that X = 1 20% of the time
It predicts that X = 0 80% of the time
So that means:
True Positive : 40% * 20% = 8%
True Negative : 40% * 80% = 32%
False Positive: 60% * 20% = 12%
False Negative: 60% * 80% = 48%
Now my question is whether it would be correct to assume to say that the probability for a positive result using the model would be 56% (True Positive + False Negative) and the probability for a negative result using the model would be 44%(True Negative + False Positive).