On Wed, Sep 11, 2013 at 12:22 AM, Parimi Rohit rohit.par...@gmail.comwrote:
1. Do we have to follow this setting, to compare algorithms? Can't we
report the parameter combination for which we get highest mean average
precision for the test data, when trained on the train set, with out any
On Wed, Sep 11, 2013 at 12:07 AM, Sean Owen sro...@gmail.com wrote:
2. Do we have to tune the similarityclass parameter in item-based CF?
If
so, do we compare the mean average precision values based on validation
data, and then report the same for the test set?
Yes you are
Hi All,
I was wondering if there is any experimental design to tune the parameters
of ALS algorithm in mahout, so that we can compare its recommendations with
recommendations from another algorithm.
My datasets have implicit data and would like to use the following design
for tuning the ALS
You definitely need to separate into three sets.
Another way to put it is that with cross validation, any learning algorithm
needs to have test data withheld from it. The remaining data is training
data to be used by the learning algorithm.
Some training algorithms such as the one that you
