I am calculating accuracy results from a single feature using LDA. I am very curious why a certain feature consistently performs at less than chance when calculating accuracy using a stratified 10-fold cross validation technique. I have an equally distributed binary class and performing multiple xvals results in an accuracy that fluctuates fairly tightly around 0.3.
This means the training data is consistently setting a boundary which when tested against is basically the opposite of what was trained on.
I am performing this stratified 10-fold xval 10-20 times and I would expect this to fluctuate around 0.5, but it is fairly static around the 0.3 to 0.4 area.
Thanks for the help!