本文整理匯總了Java中com.rapidminer.operator.clustering.CentroidClusterModel.setClusterAssignments方法的典型用法代碼示例。如果您正苦於以下問題：Java CentroidClusterModel.setClusterAssignments方法的具體用法？Java CentroidClusterModel.setClusterAssignments怎麽用？Java CentroidClusterModel.setClusterAssignments使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類com.rapidminer.operator.clustering.CentroidClusterModel的用法示例。
在下文中一共展示了CentroidClusterModel.setClusterAssignments方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Java代碼示例。
示例1: assinePoints
import com.rapidminer.operator.clustering.CentroidClusterModel; //導入方法依賴的package包/類
/**
* assign the Points to cluster
*
* @param model
* @return
*/
private CentroidClusterModel assinePoints(CentroidClusterModel model) {
double[] values = new double[attributes.size()];
int i = 0;
for (Example example : exampleSet) {
double[] exampleValues = getAsDoubleArray(example, attributes, values);
double nearestDistance = measure.calculateDistance(model.getCentroidCoordinates(0), exampleValues);
int nearestIndex = 0;
int id = 0;
for (Centroid cr : model.getCentroids()) {
double distance = measure.calculateDistance(cr.getCentroid(), exampleValues);
if (distance < nearestDistance) {
nearestDistance = distance;
nearestIndex = id;
}
id++;
}
centroidAssignments[i] = nearestIndex;
i++;
}
model.setClusterAssignments(centroidAssignments, exampleSet);
return model;
}
示例2: assinePoints
import com.rapidminer.operator.clustering.CentroidClusterModel; //導入方法依賴的package包/類
/**
* assign the Points to cluster
*
* @param model
* @return
*/
private CentroidClusterModel assinePoints(CentroidClusterModel model) {
double[] values = new double[attributes.size()];
int i = 0;
for (Example example : exampleSet) {
double[] exampleValues = getAsDoubleArray(example, attributes,
values);
double nearestDistance = measure.calculateDistance(
model.getCentroidCoordinates(0), exampleValues);
int nearestIndex = 0;
int id = 0;
for (Centroid cr : model.getCentroids()) {
double distance = measure.calculateDistance(cr.getCentroid(),
exampleValues);
if (distance < nearestDistance) {
nearestDistance = distance;
nearestIndex = id;
}
id++;
}
centroidAssignments[i] = nearestIndex;
i++;
}
model.setClusterAssignments(centroidAssignments, exampleSet);
return model;
}