Re: Why does `kNearestNeighbours` return more neighbours than `m_kNN` specified?

I think that there is an issue on IBk cross validation.

Let's suppose we change the previous step 6 into this one: 
weka.classifiers.lazy.IBk -K 17 -W 0 -X -E -A 
"weka.core.neighboursearch.LinearNNSearch -A 
\"weka.core.EuclideanDistance -D -R first-4\" -S" -output-debug-info. In 
Classifier output will appear 
<https://git.cms.waikato.ac.nz/weka/weka/-/blob/3cbb52f2172daeab749aedd5afbe1463775ca361/trunk/weka/src/main/java/weka/classifiers/lazy/IBk.java#L805-810>:

IB1 instance-based classifier
using 5 nearest neighbour(s) for classification

But this is not true. Because that kis calculated considering /all/ 
instances in dataset without splitting it in two sets: training and 
test. WEKA is cheating like a student that sees a test before the exam. 
WEKA sees test set.
But that value will be ignored when WEKA will do predictions on test 
set. So where do you find the “honest” knamely it calculated based only 
on training set? Well, you must read the output of terminal and find the 
last Selected k = 
<https://git.cms.waikato.ac.nz/weka/weka/-/blob/3cbb52f2172daeab749aedd5afbe1463775ca361/trunk/weka/src/main/java/weka/classifiers/lazy/IBk.java#L1007> 
string. This is possible because we add the option -output-debug-infoto 
IBk. In my case, it was 4.

I think that this behaviour is misleading. It can confuse the user also 
because there are no info, disclaimer or pop-up about it.

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