[scikit-learn] I’m in trouble and I need your advice on operating scikit-learn

[PARK Jinwoo]

Dear scikit-learn experts

Hello, I am a graduate school student majoring in doping control
analysis in Korea.
Now I'm in a research institute that carries out doping control analyses.

I received a project by my advising doctor. It's about operating an AI
project.
A workshop is scheduled in April, so it needs to be done in a month.
However, I haven't learn computer science at all and I'm totally ignorant
of it.
So I desperately need your advice.

To be specific, the 3 xml files shown in the picture are analysis results
named positive, negative, and unknown from top to bottom.
We'd like to let AI learn positive and negative data,
input unknown datum, and then see what result will turn out.

I came to know that there's a module called 'iris calssification' in
scikit-learn
and I'm thinking of utilizing that as it seems similar with my assignment
However, while the database of iris is a csv file with 150 data and
labels inside,
what I have are 3 xml files each one of which represents one data,
which are stored in C:\Users\Jinwoo\Documents\Python Scripts\mzdata
The training process is not shuffling randomly the 150 data and
dividing into training set and test set. The data are already assigned
into training ones and testing one.
Also, when training the program, training labels naming positive and
negative should be inserted on my own.

What I know all is that it will be appropriate to use fit() function
and predict() function to train and test.
But I have no idea on what to import, how to write codes correctly, and so
on

It will be thankful to give me some help.

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