I am using the R caret package to build a randomforest classifier model for plant data.
The dataset has 7 variables - all numeric which are being used to predict if a plant will "grow" or "not grow".
This is a very simple model.
In my training dataset I have 70% of observations classified as "grow" and 30% classified at "not grow".
I have trained the model using this data and have received an accuracy of 93% and a kappa of 86%.
My question is about the Mcnemar's Test: I have a p-value of 0.8231 which I understand usually means I reject the Null hypothesis.
I have attempted to research this test and it appears to be something about proportion change before and after an event.
Would I be correct in saying this has something to do with my imbalanced proportion in my dependent variable?
Could anyone interpret this p-value?