How to use

NumericVectorFeature

in

com.oculusinfo.ml.feature.numeric

@Override
public NumericVectorFeature getCentroid() {
  // create the centroid geospatial feature set
  NumericVectorFeature mean = new NumericVectorFeature(name);
  
  mean.setValue(meanVector);
  mean.setWeight(weight);
      
  return mean;
}

@Override
public String toString() {
  return (this.getName() + ":" + vectorToString());
}

@Override
public void remove(NumericVectorFeature feature) {
  double removedWeight = feature.getWeight();
  double newWeight = weight - removedWeight;
  if (0.0 == weight) return;
  // decrement centroid vector
  for (int i=0; i < meanVector.length; i++) {
    meanVector[i] = (meanVector[i] * weight - feature.getValue()[i] * removedWeight) / newWeight;
  }
  weight = newWeight;
}

  public NumericVectorFeature fieldToNumericVectorFeature(String name) {
    Field field = fields.get(name);
    
    if (field == null) return null;
    
    NumericVectorFeature feature = null;
    
    try {
      feature = new NumericVectorFeature(field.name);
    
      String val = field.value.substring(1, field.value.length()-1);  // strip off enclosing [ ]
    
      if (val.isEmpty()) return null;
      
      String[] entries = val.split(";");
    
      double[] vector = new double[entries.length];
    
      for (int i=0; i < entries.length; i++) {
        if (entries[i].isEmpty()) continue;
        vector[i] = Double.parseDouble(entries[i]);
      }
      feature.setValue(vector);
    }
    catch (Exception e) {
      e.printStackTrace();
    }    
    return feature;
  }
}

public void setValue(List<Double> vector) {
  setValue(new ArrayList<Double>(vector));
}

  @Override
  public double distance(NumericVectorFeature x, NumericVectorFeature y) {
    double[] vector1 = x.getValue();
    double[] vector2 = y.getValue();
    
    double d = 0;
    for (int i = 0; i < vector1.length; i++) {
      d += Math.pow(vector1[i] - vector2[i], 2);
    }
    
    // return euclidean distance
    return Math.sqrt( d / (double)vector1.length );
  }
}

double[] meanVector = ((NumericVectorFeature)allFeatures.get(0)).getValue().clone();
  double[] vals = v.getValue();
  double[] vals = v.getValue();
  double[] vals = v.getValue();

@Override
public void add(NumericVectorFeature feature) {
  double addedWeight = feature.getWeight();
  double newWeight = weight + addedWeight;
  if (meanVector == null) {
    if (feature.getValue() != null) {
      meanVector = feature.getValue().clone();
      weight = addedWeight;
    }
  }
  else {
    if (feature.getValue() != null) {
      // incrementally revise the centroid vector
      for (int i=0; i < meanVector.length; i++) {
        meanVector[i] = (meanVector[i] * weight + feature.getValue()[i] * addedWeight) / newWeight;
      }
      weight = newWeight;
    }
  }
}