java.lang.Exception: Problem with options to 'LearnModel'.

Google Groups | Zara Rezaie | 4 months ago
  1. 0

    "Not found class moa.DoTask" problem while using weka classifiers

    Google Groups | 4 months ago | Zara Rezaie
    java.lang.Exception: Problem with options to 'LearnModel'.
  2. 0

    Problem with Evaluate prequential on singleclassifier using command line

    Google Groups | 2 years ago | Abril Uriarte
    java.lang.Exception: Problem with options to 'EvaluatePrequential'. Valid options for EvaluatePrequential: -l learner (default: bayes.NaiveBayes) Classifier to train. -s stream (default: generators.RandomTreeGenerator) Stream to learn from. -e evaluator (default: WindowClassificationPerformanceEvaluator) Classification performance evaluation method. -i instanceLimit (default: 100000000) Maximum number of instances to test/train on (-1 = no limit). -t timeLimit (default: -1) Maximum number of seconds to test/train for (-1 = no limit). -f sampleFrequency (default: 100000) How many instances between samples of the learning performance. -q memCheckFrequency (default: 100000) How many instances between memory bound checks. -d dumpFile File to append intermediate csv results to. -o outputPredictionFile File to append output predictions to. -w width (default: 1000) Size of Window -a alpha (default: 0.01) Fading factor or exponential smoothing factor -O taskResultFile File to save the final result of the task to.
  3. 0

    Run Weka Classifiers through MOA

    Stack Overflow | 2 years ago
    java.lang.Exception: Problem creating instance of class: LearnModel
  4. Speed up your debug routine!

    Automated exception search integrated into your IDE

  5. 0

    Input file

    Google Groups | 1 year ago | Domenico Mancuso
    java.lang.Exception: Problem with options to 'EvaluatePrequentialRegression'. Valid options for EvaluatePrequentialRegression: -l learner (default: trees.FIMTDD) Classifier to train. -s stream (default: generators.RandomTreeGenerator) Stream to learn from. -e evaluator (default: WindowRegressionPerformanceEvaluator) Classification performance evaluation method. -i instanceLimit (default: 100000000) Maximum number of instances to test/train on (-1 = no limit). -t timeLimit (default: -1) Maximum number of seconds to test/train for (-1 = no limit). -f sampleFrequency (default: 100000) How many instances between samples of the learning performance. -q memCheckFrequency (default: 100000) How many instances between memory bound checks. -d dumpFile File to append intermediate csv results to. -o outputPredictionFile File to append output predictions to. -w width (default: 1000) Size of Window -a alpha (default: 0.01) Fading factor or exponential smoothing factor -O taskResultFile File to save the final result of the task to.
  6. 0

    GitHub comment 35#33561466

    GitHub | 3 years ago | l0huan08
    java.lang.Exception: Class not found: ClusterEvaluation

    Not finding the right solution?
    Take a tour to get the most out of Samebug.

    Tired of useless tips?

    Automated exception search integrated into your IDE

    Root Cause Analysis

    1. java.lang.Exception

      Class not found: WekaClassifier

      at moa.options.ClassOption.cliStringToObject()
    2. moa.options
      ClassOption.cliStringToObject
      1. moa.options.ClassOption.cliStringToObject(ClassOption.java:128)
      2. moa.options.ClassOption.setValueViaCLIString(ClassOption.java:67)
      3. moa.options.Options.setViaCLIString(Options.java:145)
      4. moa.options.ClassOption.cliStringToObject(ClassOption.java:154)
      4 frames
    3. moa
      DoTask.main
      1. moa.DoTask.main(DoTask.java:130)
      1 frame