Quick start

Warning

This package is python wrapper for java library called RuleKit. This means it requires java JRE in version 1.8.0 to be installed to run. You also need JAVA_HOME environmental variable to be set. Package should work fine with both Oracle and Open JDK.

Installation

pip install rulekit
python -m rulekit download_jar

Note

Second command will download RuleKit jar file from github releases. This step is required to use this package.

To check if everything was installed correctly call:

import rulekit
rulekit.__version__

It should run without errors and print package version.

Package usage

Now we are finally ready to use rulekit package and its models.

from  sklearn import  datasets
from rulekit import RuleKit
from rulekit.classification import RuleClassifier

iris=datasets.load_iris()
X=iris.data
y=iris.target

classifier = RuleClassifier()
classifier.fit(X, y)

prediction = classifier.predict(X)

from sklearn.metrics import accuracy_score

print('Accuracy: ', accuracy_score(y, prediction))

As you may noticed, training and using rulekit models is the same as in scikit learn. This mean you can use scikit: metrics, cross-validation, hyper-parameters tuning etc. with ease.

For more examples head to Tutorials section.