Hi, On Tue, Mar 27, 2012 at 6:05 AM, Alekseiy Beloshitskiy <abeloshits...@velti.com> wrote: > Hi All, > > Here is the case. I want to build classification model (SVM). Some of > variables for this model are categorical attributes which represent words > (usually 3-10 words - query for search in google). For example: > search_id | query_words |..| result > -----------+----------------------------------+--+-------- > 1 | how,to,grow,tree |..| 4 > 2 | smartfone,htc,buy,price |..| 7 > 3 | buy,house,realty,london |..| 6 > 4 | where,to,go,weekend,cinema |..| 4 > ... > As you can see, words in the query are disordered and may occur in different > queries. Total number of unique words for all queries is several thousands. > The question is how to represent this variable (query_words) to use for SVM. > > Thank you for any advices!
One approach is to wire up a "bag of words" type of design matrix. That is to say the matrix has as many columns as there are unique words. Each row is an observation (query), and the words that appear in the query have a value of 1 (or you can count the number of times each word appears). You can maybe get smarter and try to group like words together, but ... now you'll have two problems ... Hope you have lots of data! -steve -- Steve Lianoglou Graduate Student: Computational Systems Biology | Memorial Sloan-Kettering Cancer Center | Weill Medical College of Cornell University Contact Info: http://cbio.mskcc.org/~lianos/contact ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
