To evaluate the performance a new classifier algorithm, I'm trying to compare the accuracy and the complexity (big-O in training and classifying). From Machine Learning: a review I get a complete supervised classifiers list, also a accuracy table between the algorithms, and 44 test problems from UCI data repositoy. However, I can't find a review, paper or web-site with the big-O for common classifiers like:
- RIPPER (I think this might not be possible, but who knows)
- ANN with Back Propagation
- Naive Bayesian
If anyone has any expression for these classifiers, it will be very useful, thank you.