I am running a binary LASSO logistic regression using glmnet. The initial data I work with is raster spatial data. When I create an ROC (AUC ~ 0.72) curve based on the test data, the resulting curve appears to curve early and has a very strange shape (shown below).
Does anyone know how I can interpret this curve and apply changes to my model to improve it?
When I generate the ROC using the training data (AUC ~ 0.93), it does not appear like this.
Also, when I run the same script on coarser resolution data (30 m as opposed to the 5 m currently being used), AUC curves on training and testing data look as expected (AUC's of ~0.94 and 0.90).