protected void updateMinDistance(double[] minDistance, boolean[] selected, Instances data, Instance center) { for (int i = 0; i < selected.length; i++) { if (!selected[i]) { double d = distance(center, data.instance(i)); if (d < minDistance[i]) { minDistance[i] = d; } } } }
protected void updateMinDistance(double[] minDistance, boolean[] selected, Instances data, Instance center) { for (int i = 0; i < selected.length; i++) { if (!selected[i]) { double d = distance(center, data.instance(i)); if (d < minDistance[i]) { minDistance[i] = d; } } } }
/** * clusters an instance that has been through the filters * * @param instance the instance to assign a cluster to * @return a cluster number */ protected int clusterProcessedInstance(Instance instance) { double minDist = Double.MAX_VALUE; int bestCluster = 0; for (int i = 0; i < m_NumClusters; i++) { double dist = distance(instance, m_ClusterCentroids.instance(i)); if (dist < minDist) { minDist = dist; bestCluster = i; } } return bestCluster; }
/** * clusters an instance that has been through the filters * * @param instance the instance to assign a cluster to * @return a cluster number */ protected int clusterProcessedInstance(Instance instance) { double minDist = Double.MAX_VALUE; int bestCluster = 0; for (int i = 0; i < m_NumClusters; i++) { double dist = distance(instance, m_ClusterCentroids.instance(i)); if (dist < minDist) { minDist = dist; bestCluster = i; } } return bestCluster; }