Need help running JRip

[Juan José Expósito González]

Hi!

After having installed python-weka-wrapper, I want to run RIPPER on a dataset. The data is already filtered and features removed and all saved into a .csv file.

I have followed the steps in the docs but I get errors:

from weka.core.classes import from_commandline

from weka.core.converters import Loader

from weka.classifiers import Classifier

from random import randint

def load_file_to_classify(url:str) -> Any:

    """Load the file to classify"""

    loader = Loader(classname = 'weka.core.converters.CSVLoader')

    data = loader.load_file(url)  # type: ignore

    data.class_is_last()

    return data

def run_weka_Jrip(url:str, num_iterations: int = 1) -> None:

    """Run the weka JRip algorithm"""

    data = load_file_to_classify(url)

    seed = randint(1, num_iterations)

   

    jrip = Classifier("weka.classifiers.rules.JRip")

    jrip.build_classifier(data)

    rset = jrip.wrapper.getRuleset()

    for i in range(rset.size()):

        print(rset.get(i))

I get the error: AttributeError: 'Classifier' object has no attribute 'build_classifier'. And I can't import Evaluation from weka.classifiers.

Any ideas?

Kindest Regards,

JJ

[Peter Reutemann]

Please post the output of "pip freeze" from the environment that you are running the script with.

And the full error message output from the console.

Cheers, Peter

--
Peter Reutemann
Dept. of Computer Science
University of Waikato, Hamilton, NZ
Mobile +64 22 190 2375
https://www.cs.waikato.ac.nz/~fracpete/
http://www.data-mining.co.nz/

14/01/2024 12:02:38 Juan José Expósito González <jjeg...@gmail.com>:

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[Juan José Expósito González]

Hi Peter, already solved! I don't know why I had done pip install weka...that messed up everything! Returned to normal and now it is working fine. I am using this code to get RIPPER rules:

def run_weka_Jrip(url: str, num_iterations: int = 1) -> list[str]:

    """Run the weka JRip algorithm"""

    data = load_file_to_classify(url)

    seed = 1

    optimizations = 2

    options = f"-F 3 -N 2.0 -O {optimizations} -S {seed}".split()

    # cmdline: str = "weka.classifiers.rules.JRip -F 3 -N 2.0 -O 2 -S 1"

    # jrip = from_commandline(cmdline)  # type: ignore

    jrip = Classifier(classname="weka.classifiers.rules.JRip", options=options)

    jrip.build_classifier(data)

    print(jrip)

And I get 4 rules, but they are different from the same rules obtained from the GUI: I have done the data split with pandas (not sure if this is correct or I should do the split in the same fashion as with WEKA GUI). These are the options I have in the GUI:

How can I get the rules in a list of strings?

Thanks!

JJ

[Peter Reutemann]

Train/test split:
https://fracpete.github.io/python-weka-wrapper3/weka.core.html#weka.core.dataset.Instances.train_test_split

Retrieving jrip rules requires accessing the underlying Java object:
https://github.com/fracpete/python-weka-wrapper3-examples/blob/ec445f4c79db25f0649692d2b5d0a0d7164e2d20/src/wekaexamples/classifiers/classifiers.py#L271

Cheers, Peter

--
Peter Reutemann
Dept. of Computer Science
University of Waikato, Hamilton, NZ
Mobile +64 22 190 2375
https://www.cs.waikato.ac.nz/~fracpete/
http://www.data-mining.co.nz/

14/01/2024 14:37:19 Juan José Expósito González <jjeg...@gmail.com>:

To view this discussion on the web visit https://groups.google.com/d/msgid/python-weka-wrapper/ce843b1f-7cc0-493e-aae0-8ef01e80e481n%40googlegroups.com.

[Peter Reutemann]

If you're just after evaluating a dataset, you can also use this method for performing a train/test split:

https://fracpete.github.io/python-weka-wrapper3/weka.html#weka.classifiers.Evaluation.evaluate_train_test_split

Cheers, Peter

--

My Open Source Blog - http://open.fracpete.org

[Juanjo]

Thanks! It works like a charm!

Kindest Regards,

JJ

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