Re: WEKA Documentation
ted pedersen <tpederse <at> d.umn.edu>
2005-01-03 07:13:05 GMT
I recommend the book :
Data Mining: Practical Machine Learning Tools and Techniques with Java
Implementations by Ian H. Witten, Eibe Frank
http://www.cs.waikato.ac.nz/~ml/weka/book.html
Yes, I know this is sort of obvious and maybe not what you think you want,
but if you are teaching an undergrad class in machine learning, you really
do want this book. It's great. It's clear, it's concise, and it's even
sort of fun. I routinely refer students who are new to machine learning to
this book and they like it - they can understand it and it doesn't even
cost too much (compared to other Machine Learning books that shall remain
nameless ;) Besides, it's written with Weka in mind. It may not include
all the latest bells and whistles in Weka, but in an undergrad class
you'll probably be dealing with decision trees and Naive Bayesian
classifiers, etc. rather than freaky kernels and the like.
Also, I think Weka is an excellent choice for a classroom tool. It's
stable, easy to use, and has lots of room for growth. So it doesn't limit
very bright or ambitious students, while not being impossible for the more
average ones.
Cordially,
Ted
On Mon, 3 Jan 2005, Dr. Arie Ben David wrote:
> Hi everyone
> I am considering using WEKA as a software tool for an undergraduate course in machine learning (we
currently use Clementine). Can you kindly recommend a web site where students can find theoretical
background, updated description, examples, bibliography, etc of all (or most) models which are
currently used in WEKA (I am not talking about object level details).
> Thank you
> Happy New Year
> Dr. Arie Ben David
>
>
>
--
Ted Pedersen
http://www.d.umn.edu/~tpederse