Important bug in percentage split for classification models

Jastrade <[email protected]> Fri, 30 Dec 2022 11:18:39 +0100
Newsgroups gmane.comp.ai.weka
Message-ID <CAGNvjsf_pXM-3cGnshob_=pi58Vcge9Kijq9OL8WBTNrY3RYbQ@mail.gmail.com>
Dear sirs,



I am noticing something wrong in Weka version 3.8.6, that I think it is
worth to describe and ask for explanation or solution if that is a bug. The
example shown is with the classifier RepTree but it happens the same with
the others.



I am using percentage split 66%, and here you see the results


[image: 2022-12-30_11h02_45.png]




   - It stays that the classification has been applied to the full training
   test, and it shows the results (for example the first) as:
   (1063/88)[528/53].
   - Total of instances is 1063+528 = 1588. Then according to that, it
   splits the data in 66%/33% correctly.



But look at what happens if I do the same but changing the pertentage split
to 80%


[image: 2022-12-30_11h07_14.png]



Basically the results are exactly the same, and it also shows in the
different rules, that it doesn´t split 80/20, but still the same 66/33 as
before.



So I have the following questions:



   1. Does this mean that it is always splitting the 66/33 by defauld,
   whatever you specify?
   2. Is it that maybe these rules are the result of using all data as
   training set in reality?



I have seen if I press to More options, that I can click on “Output models
for training splits”, and then it shows also other results, only using the
% of data indicated in Pertentage split, but again, using those data, it
shows results again splited 66/33%, as you see here:


[image: 2022-12-30_11h09_57.png]ç

[image: 2022-12-30_11h11_11.png]




So it is really confusing for me what is this doing in reality…



Can you please clarify?



Thank you very much in advance,



Best regards,


Jastrade

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