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Hyperparameters in Meka Agorithms#279

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alinevalle asked this question inQ&A
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Hello,

I'm trying to use Scikit-Multilearn to work with MEKA algorithms. I need to pass hyperparameters to both the multi-label and single-label algorithms. Here's my code:

from skmultilearn.ext import download_mekameka_classpath = download_meka()
from skmultilearn.dataset import load_datasetx_train, y_train, _, _ = load_dataset('scene', 'train')x_test, y_test, _, _ = load_dataset('scene', 'test')
from skmultilearn.ext import Mekameka = Meka(        meka_classifier = "meka.classifiers.multilabel.BR",        weka_classifier = "weka.classifiers.functions.MultilayerPerceptron -- -L 0.3 -N 500",         meka_classpath = meka_classpath,         java_command = 'C:/Program Files/Java/jdk-11.0.10/bin/java' )
meka.fit(x_train, y_train)predictions = meka.predict(x_test)

I have a problem with the prediction. The error "list index out of range" occurs. I have liac-arff installed.

Can someone help me?

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@alinevalle
Converted from issue

This discussion was converted from issue #243 on March 14, 2023 16:49.

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