本文整理了Java中gov.sandia.cognition.math.matrix.Vector.euclideanDistance()方法的一些代码示例，展示了Vector.euclideanDistance()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Vector.euclideanDistance()方法的具体详情如下：
包路径：gov.sandia.cognition.math.matrix.Vector
类名称：Vector
方法名：euclideanDistance

Vector.euclideanDistance介绍

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代码示例

代码示例来源：origin: algorithmfoundry/Foundry

/**
   * Evaluates the Euclidean distance between the two given vectors.
   *
   * @param  first The first Vector.
   * @param  second The second Vector.
   * @return The Euclidean distance between the two given vectors.
   */
  public double evaluate(
    Vectorizable first, 
    Vectorizable second)
  {
    return first.convertToVector().euclideanDistance(
      second.convertToVector());
  }
}

代码示例来源：origin: algorithmfoundry/Foundry

/**
   * Evaluates the Euclidean distance between the two given vectors.
   *
   * @param  first The first Vector.
   * @param  second The second Vector.
   * @return The Euclidean distance between the two given vectors.
   */
  public double evaluate(
    Vectorizable first, 
    Vectorizable second)
  {
    return first.convertToVector().euclideanDistance(
      second.convertToVector());
  }
}

代码示例来源：origin: gov.sandia.foundry/gov-sandia-cognition-learning-core

/**
   * Evaluates the Euclidean distance between the two given vectors.
   *
   * @param  first The first Vector.
   * @param  second The second Vector.
   * @return The Euclidean distance between the two given vectors.
   */
  public double evaluate(
    Vectorizable first, 
    Vectorizable second)
  {
    return first.convertToVector().euclideanDistance(
      second.convertToVector());
  }
}

代码示例来源：origin: algorithmfoundry/Foundry

double diff = mean.euclideanDistance(otherMean);
if (minDiff > diff)

代码示例来源：origin: gov.sandia.foundry/gov-sandia-cognition-learning-core

double diff = mean.euclideanDistance(otherMean);
if (minDiff > diff)

代码示例来源：origin: algorithmfoundry/Foundry

double diff = mean.euclideanDistance(otherMean);
if (minDiff > diff)