java.lang.Exception: Problem with options to 'EvaluateModel'. Valid options for EvaluateModel: -m model (default: LearnModel) Classifier to evaluate. -s stream (default: generators.RandomTreeGenerator) Stream to evaluate on. -e evaluator (default: BasicClassificationPerformanceEvaluator) Classification performance evaluation method. -i maxInstances (default: 1000000) Maximum number of instances to test. -o outputPredictionFile File to append output predictions to. -O taskResultFile File to save the final result of the task to.

Google Groups | D Razz | 1 year ago
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  1. 0

    Using MOA command line

    Google Groups | 1 year ago | D Razz
    java.lang.Exception: Problem with options to 'EvaluateModel'. Valid options for EvaluateModel: -m model (default: LearnModel) Classifier to evaluate. -s stream (default: generators.RandomTreeGenerator) Stream to evaluate on. -e evaluator (default: BasicClassificationPerformanceEvaluator) Classification performance evaluation method. -i maxInstances (default: 1000000) Maximum number of instances to test. -o outputPredictionFile File to append output predictions to. -O taskResultFile File to save the final result of the task to.
  2. 0

    How to use MEKAClaffier in MOA (command line)

    Google Groups | 1 year ago | Arif Pathan
    java.lang.IllegalArgumentException: Problems with option: baseLearner at moa.options.WEKAClassOption.setValueViaCLIString(WEKAClassOption.java:80)

    Root Cause Analysis

    1. java.lang.IllegalArgumentException

      Problems with option: baseLearne

      at moa.options.WEKAClassOption.setValueViaCLIString()
    2. moa.options
      WEKAClassOption.<init>
      1. moa.options.WEKAClassOption.setValueViaCLIString(WEKAClassOption.jav:80)
      2. moa.options.AbstractOption.resetToDefault(AbstractOption.java:98)
      3. moa.options.AbstractClassOption.<init>(AbstractClassOption.java:93)
      4. moa.options.AbstractClassOption.<init>(AbstractClassOption.java:72)
      5. moa.options.WEKAClassOption.<init>(WEKAClassOption.java:48)
      5 frames
    3. moa.classifiers.meta
      WEKAClassifier.<init>
      1. moa.classifiers.meta.WEKAClassifier.<init>(WEKAClassifier.java:49)
      1 frame
    4. moa.classifiers.multilabel
      MEKAClassifier.<init>
      1. moa.classifiers.multilabel.MEKAClassifier.<init>(MEKAClassifier.java37)
      1 frame