someone tried to implement SVM in a summer google code but it turns out map
reduced version of svm is too difficult to implement and they dropped the
project.
I bet you can train via libsvm and use just classification part with map
reduce but if I have a choice I prefer logistic regression too
I am currently using naive bayes for text classification.
I prefer NB over SVM because;
- SVM has long training time
- NB can be incremental
- NB can be fully parallel
the main decisions you should make while using NB is using tf or tfidf and
using binary NB or multinomial
if you classify short
hello;
i searched wiki and the web but couldn't find the reason why theta
normalization is commented out for naive bayes classification.
there is a todo comment on top that states this will be enabled soon.
is there any schedule for this?
do anyone know the reason not to use theta normalization?
