We need to decide between Support Vector Machines and Fast Artificial Neural Network for some text processing project.
It includes Contextual Spelling Correction and the
I think you'll get a competitive results from both of the algorithms, so you should aggregate the results... think about ensemble learning.
Update:
I don't know if this is specific enough: use Bayes Optimal Classifier to combine the prediction from each algorithm. You have to train both of your algorithms, then you have to train the Bayes Optimal Classifier to use your algorithms and make optimal predictions based on the input of the algorithms.
Separate your training data in 3:
Update 2.0:
Another way to create an ensemble of the algorithms is to use 10-fold (or more generally, k-fold) cross-validation:
Remember that you can generally combine many the classifiers and validation methods in order to produce better results. It's just a matter of finding what works best for your domain.