Mallet vs. Weka for text classification

Question

Which product (Mallet or Weka) is better suited for the task of classifying text:

• Simplify learning
• top scores
• Documentation

I am new to this problem so any comments would be great

Answer 1

MALLET is much easier to use and does most of its work unnoticed. You also do not need to convert the format to anything, you just give it text files and this gives you the results.

Weka requires converting text to a specific format (Weka script is so slow and inefficient for this that I would recommend you write your own).

The problem with MALLET is that the training uses GB of memory, and this can take several hours if you have large training sets.

Weka has more documentation, but most of them make no sense. MALLET has very little documentation, but is very easy to use.

Honestly, after testing both of them, I decided to write my own classifier.

Answer 2

I really like Weka vs Mallet. Maybe I don’t know enough yet, but doing machine learning using the GUI is awesome. You can adjust the parameters and run various experiments (it is also easy to track the results of past experiments in front of you). I am new to Weka, so this is FWIW.

How much easier it is to train, I find Weka easier. I don’t know what control you can have over your space of objects by simply pointing Mallet to some text (maybe this is good enough), but my experience with Mallet was comparable to Weka ... writing scripts to enter the input in the proper format, with the caveat that I had to take a few steps to use some kind of serialized version of the data in Mallet.

As for your other questions, I cannot answer them right now, but I hope that this answer will not be canceled, because in any case there will be good information.