My training data is weighed heavier on the '1' class, with about a 4:6 ratio. This outputs a classifier that is of 82% accuracy with an emphasis on the '1' class, which makes sense.
Confusion Matrix - [[333 133] [ 62 612]]
I have the test proportions as well, in which the data will be tested on, which is 0.3 of '1' and 0.7 of '0' or 1900 0s and 900 1s. My classifier outputs 1400 1s and 1300 0s.
My theory is that I need to build a classifier that favours the '0', If so how can I make the classifier biased to one class over another?
I have tried to used the class weights, this does increase the '0' predictions but only by a very small percentage.