weka.core.Utils.maxIndex()方法的使用及代码示例

x33g5p2x  于2022-02-01 转载在 其他  
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本文整理了Java中weka.core.Utils.maxIndex()方法的一些代码示例，展示了Utils.maxIndex()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。Utils.maxIndex()方法的具体详情如下：
包路径：weka.core.Utils
类名称：Utils
方法名：maxIndex

Utils.maxIndex介绍

[英]Returns index of maximum element in a given array of doubles. First maximum is returned.
[中]返回给定双精度数组中最大元素的索引。返回第一个最大值。

代码示例

代码示例来源：origin: nz.ac.waikato.cms.weka/weka-stable

double eval(double[] args) {
 return args[Utils.maxIndex(args)];
}

代码示例来源：origin: Waikato/weka-trunk

double eval(double[] args) {
 return args[Utils.maxIndex(args)];
}

代码示例来源：origin: net.sf.meka/meka

/**
 * Convert Distribution - Given the posterior across combinations, return the distribution across labels.
 * @param    p    the posterior of the super classes (combinations), e.g., P([1,3],[2]) = [1,0]
 * @param    L     the number of labels
 * @return    the distribution across labels, e.g., P(1,2,3) = [1,0,1]
 */
public static final double[] recombination(double p[], int L, LabelSet map[]) {
  double y[] = new double[L];
  int i = Utils.maxIndex(p);
  LabelSet y_meta = map[i]; 
  for(int j : y_meta.indices) {
    y[j] = 1.0;
  }
  return y;
}

代码示例来源：origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Computes log of density for given value.
 */
public double logDensity(double value) {
 double[] a = logJointDensities(value);
 double max = a[Utils.maxIndex(a)];
 double sum = 0.0;
 for(int i = 0; i < a.length; i++) {
  sum += Math.exp(a[i] - max);
 }
 return max + Math.log(sum);
}

代码示例来源：origin: nz.ac.waikato.cms.moa/moa

@Override
public double[] getClassVotes(Instance instance) {
  double[] votes = super.getClassVotes(instance);
  this.lastPrediction = Utils.maxIndex(votes);
  return votes;
}

代码示例来源：origin: Waikato/weka-trunk

/**
 * Computes log of density for given value.
 */
public double logDensity(double value) {
 double[] a = logJointDensities(value);
 double max = a[Utils.maxIndex(a)];
 double sum = 0.0;
 for(int i = 0; i < a.length; i++) {
  sum += Math.exp(a[i] - max);
 }
 return max + Math.log(sum);
}

代码示例来源：origin: nz.ac.waikato.cms.weka/weka-stable

/**
 * Returns the value as string out of the given distribution
 * 
 * @param c the attribute to get the value for
 * @param dist the distribution to extract the value
 * @return the value
 */
protected String sourceClass(Attribute c, double []dist) {
 if (c.isNominal()) {
  return Integer.toString(Utils.maxIndex(dist));
 } else {
  return Double.toString(dist[0]);
 }
}

代码示例来源：origin: Waikato/weka-trunk

/**
 * Returns the value as string out of the given distribution
 * 
 * @param c the attribute to get the value for
 * @param dist the distribution to extract the value
 * @return the value
 */
protected String sourceClass(Attribute c, double []dist) {
 if (c.isNominal()) {
  return Integer.toString(Utils.maxIndex(dist));
 } else {
  return Double.toString(dist[0]);
 }
}

代码示例来源：origin: nz.ac.waikato.cms.moa/moa

@Override
public double[] getVotesForInstance(Instance inst) {
  double[] Pr = new double[inst.numClasses()];
  for (int i = 0; i < this.experts.size(); i++) {
    double[] pr = this.experts.get(i).getVotesForInstance(inst);
    int yHat = Utils.maxIndex(pr);
    Pr[yHat] += this.weights.get(i);
  } // for
  Utils.normalize(Pr);
  return Pr;
}

代码示例来源：origin: Waikato/meka

/**
 * Return the argmax on #distribution(Instance, double[]).
 * @return argmax_{k in 0,1,...} p( y_j = k | x , y_pred )
 */
public double classify(Instance x, double ypred[]) throws Exception {
  Instance x_ = transform(x,ypred);
  return Utils.maxIndex(h.distributionForInstance(x_));
}

代码示例来源：origin: net.sf.meka/meka

/**
 * Return the argmax on #distribution(Instance, double[]).
 * @return argmax_{k in 0,1,...} p( y_j = k | x , y_pred )
 */
public double classify(Instance x, double ypred[]) throws Exception {
  Instance x_ = transform(x,ypred);
  return Utils.maxIndex(h.distributionForInstance(x_));
}

代码示例来源：origin: nz.ac.waikato.cms.moa/moa

@Override
public Node learnFromInstance(Instance inst) {
  double[] classVotes = getMajorityClassVotes(inst);
  double error = (Utils.maxIndex(classVotes) == (int) inst.classValue()) ? 0.0 : 1.0;
  this.majorityClassError += error;
  classVotes = getNaiveBayesPrediction(inst);
  error = (Utils.maxIndex(classVotes) == (int) inst.classValue()) ? 0.0 : 1.0;
  this.naiveBayesError += error;
  return super.learnFromInstance(inst);
}

代码示例来源：origin: nz.ac.waikato.cms.moa/moa

@Override
public Node learnFromInstance(Instance inst) {
  double[] classVote = getMajorityClassVotes(inst);
  double error = (Utils.maxIndex(classVote) == (int) inst.classValue()) ? 0.0 : 1.0;
  this.majorityClassError.input(error);
  classVote = getNaiveBayesPrediction(inst);
  error = (Utils.maxIndex(classVote) == (int) inst.classValue()) ? 0.0 : 1.0;
  this.naiveBayesError.input(error);
  return super.learnFromInstance(inst);
}

代码示例来源：origin: nz.ac.waikato.cms.moa/moa

private void updateCounters(Instance experiencia) {
  double[] classVotes = this.getClassVotes(experiencia);
  boolean trueClass = (Utils.maxIndex(classVotes) == (int) experiencia.classValue());
  if (estimator != null && ((Iadem3) this.tree).restartAtDrift) {
    double error = trueClass == true ? 0.0 : 1.0;
    this.estimator.input(error);
    if (this.estimator.getChange()) {
      this.restartVariablesAtDrift();
    }
  }
}

代码示例来源：origin: nz.ac.waikato.cms.moa/moa

private void updateCountersForChange(Instance inst) {
  double[] classVotes = this.getClassVotes(inst);
  boolean trueClass = (Utils.maxIndex(classVotes) == (int) inst.classValue());
  if (estimador != null && ((Iadem3) this.tree).restartAtDrift) {
    double error = trueClass == true ? 0.0 : 1.0;
    this.estimador.input(error);
    if (this.estimador.getChange()) {
      this.resetVariablesAtDrift();
    }
  }
}

代码示例来源：origin: nz.ac.waikato.cms.weka/meka

protected void classify(Instance x) throws Exception {
  // cut out irrelevant attributes
  Instance copy = CCUtils.linkTransformation(x,this.exl,this._template);
  // round
  for(int k = 0; k < this.j; k++) {
    copy.setValue(j,Math.round(copy.value(k)));
  }
  //set class          
  double dist[] = this.classifier.distributionForInstance(copy);  
  int max_index = (int)Utils.maxIndex(dist);		// v = max_index(dist)
  confidences[this.index] = dist[max_index];		// w_j = dist[v] = p(y_j == v)
  x.setValue(this.index,max_index);			// y_j = 0
  //carry on
  if (next!=null) next.classify(x);
}

代码示例来源：origin: nz.ac.waikato.cms.moa/moa

private void updateCounters(Instance inst) {
  double[] classVotes = this.getClassVotes(inst);
  boolean correct = (Utils.maxIndex(classVotes) == (int) inst.classValue());
  if (this.estimator != null && ((Iadem3) this.tree).restartAtDrift) {
    double error = correct == true ? 0.0 : 1.0;
    this.estimator.input(error);
    if (this.estimator.getChange()) {
      this.resetVariablesAtDrift();
    }
  }
}

代码示例来源：origin: nz.ac.waikato.cms.weka/meka

@Override
public double[] distributionForInstance(Instance x) throws Exception {
  int L = x.classIndex(); 
  double y[] = new double[L*2];
  for (int j = 0; j < L; j++) {
    Instance x_j = (Instance)x.copy();
    x_j.setDataset(null);
    x_j = MLUtils.keepAttributesAt(x_j,new int[]{j},L);
    x_j.setDataset(m_Templates[j]);
    double w[] = m_MultiClassifiers[j].distributionForInstance(x_j); // e.g. [0.1, 0.8, 0.1]
    y[j] = Utils.maxIndex(w);									     // e.g. 1
    y[L+j] = w[(int)y[j]];											 // e.g. 0.8
  }
  return y;
}

代码示例来源：origin: net.sf.meka/meka

@Override
public double[] distributionForInstance(Instance x) throws Exception {
  int L = x.classIndex(); 
  double y[] = new double[L*2];
  for (int j = 0; j < L; j++) {
    Instance x_j = (Instance)x.copy();
    x_j.setDataset(null);
    x_j = MLUtils.keepAttributesAt(x_j,new int[]{j},L);
    x_j.setDataset(m_Templates[j]);
    double w[] = m_MultiClassifiers[j].distributionForInstance(x_j); // e.g. [0.1, 0.8, 0.1]
    y[j] = Utils.maxIndex(w);									     // e.g. 1
    y[L+j] = w[(int)y[j]];											 // e.g. 0.8
  }
  return y;
}

代码示例来源：origin: Waikato/meka

@Override
public double[] distributionForInstance(Instance x) throws Exception {
  int L = x.classIndex(); 
  double y[] = new double[L*2];
  for (int j = 0; j < L; j++) {
    Instance x_j = (Instance)x.copy();
    x_j.setDataset(null);
    x_j = MLUtils.keepAttributesAt(x_j,new int[]{j},L);
    x_j.setDataset(m_Templates[j]);
    double w[] = m_MultiClassifiers[j].distributionForInstance(x_j); // e.g. [0.1, 0.8, 0.1]
    y[j] = Utils.maxIndex(w);									     // e.g. 1
    y[L+j] = w[(int)y[j]];											 // e.g. 0.8
  }
  return y;
}

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