I'm designing large-scale, regularized logistic regression models with lots of sparse, binarized features. e.g. isUS, isFR, etc. As a result, a lot of the weights in the model are zero. I'm wondering ...
For classification problems I have been using Neural Networks and measuring Type I and II error using the confusion matrix and its measures as per this resource which is pretty straight forward. ...