I believe the most reliable way to compare different classifiers in WEKA
can be accomplished using WEKA "Experimenter".
On 25 March 2016 at 22:38, Francesca Rig [via WEKA] <
I'm quite new to weka and data mining and I have to develop a project.
My idea is to use data from ended auctions of Ebay (Category of the item,
shipping cost, auction duration, condition of the item, user's feedbacks)
to build a model to predict the probability of sale of a given item.
The dataset that I have built is composed by those attributes:
and the class attribute is the "item_sold" one, with two possible values:
YES or NO.
For my purpose I was looking for a classifier that outputs the probability
that an item will belong to class YES, so that if a user inputs
"item_category,auction_duration,feedback,shipping,cost" he will then
receive as an output the probability of selling his item.
I have tried with bayesian classifiers but I am not sure they are the
right choice to this aim.
Any hint on the way I should take to find the right classifier? Is this
kind of classification problem feasible?
Thank you very much!
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