...
- LABEL_ATTRIBUTE: In the input data, which is the attribute with the label, that should be learned
- WEKA_ALGORITHM: Which WEKA Algorithm should be used. At the moment, the following algorithms are available. See WEKA for more information:
- BayesNet
- NaiveBayes
- NaiveBayesMultinomial
- NaiveBayesUpdateable
- GaussianProcesses
- Logistic
- MultilayerPerceptron
- SimpleLogistic
- SMO
- IBk
- KStar
- LWL
- DecisionTable
- JRip
- OneR
- PART
- DecisionStump
- HoeffdingTree
- J48
- LMT
- RandomForest
- RandomTree
- REPTree
- WEKA_OPTIONS: The options that should be given for the algorithm (see https://weka.sourceforge.io/doc.stable/weka/classifiers/Classifier.html for information about the given parameters)
- GROUP_BY (Optional): Grouping Attributes that should be used.
- ATTRIBUTES (Optional): Attributes that should be used for building the classifier. If not given, the input schema will be used. If not given and group_by is given, the attributes are the input attributes without the group_by attributes.
Important: EVAL_AT_NEW_ELEMENT = false, EVAL_BEFORE_REMOVE_OUTDATING = true must be provided this way. Currently, there is no check, for this and output may be wrong.
...