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Splitting Approaches #11
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What's ur rating, binary one?
On Fri, Oct 20, 2017 at 1:57 AM MatthiasKirsch ***@***.***> wrote:
I created a little dataset with the following data an tried to use
itemsplitting. It does not work, maybe the code is broken?
[image: grafik]
<https://user-images.githubusercontent.com/18574614/31808666-7e01b49a-b574-11e7-8813-930743e08de0.png>
Here the items 1, 2 and 6 are rated in different contexts so the
ItemSplitting should divide them but it doesn't. Still "0 items splitted".
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My rating has only positive values 1 because it is purchase data (no zeros available). This is why I use BPR because I think this algorithm can handle this kind of data. The BPR works fine but the ItemSplitting in front does not. |
Splitting doesn't work if u only have 1 as rarings in ur data
On Fri, Oct 20, 2017 at 6:36 AM MatthiasKirsch ***@***.***> wrote:
Yes, my rating has only positive values 1 because it is purchase data.
This is why I use BPR because I think this algorithm can handle this kind
of data. The BPR works fine but the ItemSplitting in front does not.
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Is it possible to change the implementation of Itemsplitting to make it work with positive-only data? For example, using chi2 or entropy instead of a t-test on rating deviation as splitting criteria? Can the BPR-algorithm then also work properly without negative rating? If not, what would you recommend as best-pratice for working with positive-only data? Creating dummy zeros for the very large number of unseen products? I'm concerned that this is impossible with large datasets (e.g. 10.000s of products and 100.000s of users). Thanks for any advice |
You can download source codes and modify it by yourself.
Or you can assignmen some zero ratings.
…On Fri, Oct 20, 2017 at 2:47 PM, hankej ***@***.***> wrote:
Is it possible to change the implementation of Itemsplitting to make it
work with positive-only data? For example, using chi2 instead of a t-test
on rating deviation? If not what is the best-pratice for working with
positive-only data? Creating dummy zeros for the very large number of
unseen products?
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Thanks for your reply. I don't get the point of "inventing" some zero ratings. Wouldn't this distort the results if i start assigning zero values randomly? And if i would assign a "0" to each possible user-item combination, the rating file will not fit into memory. |
In this case, it is suggested to get external/other feedback information,
such as implicit feedbacks. So that you can distinguish positive and
negative ratings.
To utilize the splitting based approaches, you should have positive and
negative feedbacks, so that they can perform the 'split'
…On Fri, Oct 20, 2017 at 5:21 PM, Jh ***@***.***> wrote:
Thanks for your reply. I don't get the point of "inventing" some zero
ratings. Wouldn't this distort the results if i start assigning zero values
randomly? And if i would assign a "0" to each possible user-item
combination, the rating file will not fit into memory.
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please , i interest to splitting approach; |
In the configuration file, there is one option: |
Hi,
I'm trying to use BPR with UISplitting. Everytime I execute the settings.conf the log tells me that there haven been 0 items/users splitted. Is this normal?
My procedure: I created two settings.conf files. One is for transforming the testset into binary format and the other one is for the real process with my trainset as trainset and the testset (transformed to binary format) as testset.
I also tried to directly use my testset as non-binary format csv-file together with the trainset but this gives me an error, so I think it might be fine to convert the testset in a first step and then use the output as new testset.
Code snippet:
After this step I extract the converted testset (now: ratings_binary.txt) from the created CARSKit.Workspace folder and put it next to my trainset. Then I deleted the CARSKit.Workspace folder and the debug.log and results.txt file.
Code snippet:
When I now run this, than it first starts converting the trainset into binary format which is fine. After doing so it starts the UISplit and it tells me
0 items have been splitted
and0 users have been splitted
. I don't know if this is okay because the process continues with bpr aftwerwards and doesn't give me an error. But this has finished and I evaluate my results and compare the context splitted results with the one only using BPR the curves seem to be very similar. So I thought it might be that I am doing something wrong here.Can you help me please :)
Thank you very much!
This is my output:
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