can it be used for usual classification problem?

[Sandy4321]

can it be used for usual classification problem when
wen each data observation is one vector
and when there are 2 classes : yes and no
in short can it be used for usual logistic regression cases?
like
https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html

[tiepvupsu]

Yes, absolutely. I'll make one example for that task.

[Sandy4321]

Great thanks,
looking forward
so it will be example for 2 classes ( let's say yes and no) for classification were each data observation is presented by vector.
Data is unbalanced data let's say 10% label yes and 90% label no
Better if this vector is spars and each element is 1 or 0
For example 80% of zeros
Then we can see clear pattern to find

For example we may have 100000 observations
When yes observations are minority for example 3000 yes observations
Then vector length is 150
We may have 15 patterns
Each pattern is 20 values long
For example
pattern 1
1111111111111111111
Pattern 2
0101010101010101010
Etc
Then let's run logistics regression from scikit learn and your code
Hopefully your code will be better?

[Sandy4321]

I see you updated to Python 3
Great thanks
It would be very kind of you to add this well deserved classification example
As well
Thanks a lot in advance