samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/common/Perceptron.java [113:127]:
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    this.nError = p.nError;
    this.fadingFactor = p.fadingFactor;
    this.learningRatio = p.learningRatio;
    this.learningRateDecay = p.learningRateDecay;
    if (p.weightAttribute != null)
      this.weightAttribute = p.weightAttribute.clone();

    this.perceptronattributeStatistics = new DoubleVector(p.perceptronattributeStatistics);
    this.squaredperceptronattributeStatistics = new DoubleVector(p.squaredperceptronattributeStatistics);
    this.perceptronInstancesSeen = p.perceptronInstancesSeen;

    this.initialisePerceptron = p.initialisePerceptron;
    this.perceptronsumY = p.perceptronsumY;
    this.squaredperceptronsumY = p.squaredperceptronsumY;
    this.perceptronYSeen = p.perceptronYSeen;
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samoa-api/src/main/java/org/apache/samoa/learners/classifiers/rules/common/Perceptron.java [134:148]:
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    this.nError = p.nError;
    this.fadingFactor = p.fadingFactor;
    this.learningRatio = p.learningRatio;
    this.learningRateDecay = p.learningRateDecay;
    if (p.weightAttribute != null)
      this.weightAttribute = p.weightAttribute.clone();

    this.perceptronattributeStatistics = new DoubleVector(p.perceptronattributeStatistics);
    this.squaredperceptronattributeStatistics = new DoubleVector(p.squaredperceptronattributeStatistics);
    this.perceptronInstancesSeen = p.perceptronInstancesSeen;

    this.initialisePerceptron = p.initialisePerceptron;
    this.perceptronsumY = p.perceptronsumY;
    this.squaredperceptronsumY = p.squaredperceptronsumY;
    this.perceptronYSeen = p.perceptronYSeen;
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