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April 2007

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Subject:
From:
Hillel Coren <[log in to unmask]>
Reply To:
Classification, clustering, and phylogeny estimation
Date:
Mon, 30 Apr 2007 10:06:36 -0400
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I'm working on the following problem and was hoping that someone in
the forum could lend a hand. I've got the following data:

publication | article | sales conversion
----------------------------------------------------
forbes | top 10 businesses | 0.283
newsweek | best 10 pet stores | 0.347
 |  | 

The goal is to use the publication and article to select future
articles which we predict will have a high sales conversion rate. I've
transformed the data into the following ARFF file.

@resource articles

@attribute publication {forbes, newsweek, ...}
@attribute top {yes, no}
@attribute 10 {yes, no}
@attribute businesses {yes, no}
@attribute best {yes, no}
@attribute pet {yes, no}
@attribute stores {yes, no}

@attribute sales_conversion NUMERIC

@data
{0 Forbes, 1 yes, 2 yes, 3 yes, 7 0.283}
{0 newsweek, 4 yes, 2 yes, 5 yes, 6 yes, 7 0.283}


What do you feel would be the best way to approach this problem (I'm
using WEKA)?

Thank you for your help,
Hillel

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