本文整理汇总了Java中com.rapidminer.operator.clustering.CentroidClusterModel.setClusterAssignments方法的典型用法代码示例。如果您正苦于以下问题：Java CentroidClusterModel.setClusterAssignments方法的具体用法？Java CentroidClusterModel.setClusterAssignments怎么用？Java CentroidClusterModel.setClusterAssignments使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类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个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: assinePoints
import com.rapidminer.operator.clustering.CentroidClusterModel; //导入方法依赖的package包/类
/**
* 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; //导入方法依赖的package包/类
/**
* 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;
}