本文整理匯總了Java中com.rapidminer.operator.clustering.CentroidClusterModel.getCentroidCoordinates方法的典型用法代碼示例。如果您正苦於以下問題：Java CentroidClusterModel.getCentroidCoordinates方法的具體用法？Java CentroidClusterModel.getCentroidCoordinates怎麽用？Java CentroidClusterModel.getCentroidCoordinates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.getCentroidCoordinates方法的5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: calcBIC
import com.rapidminer.operator.clustering.CentroidClusterModel; //導入方法依賴的package包/類
/**
* Calculate the BIC like in the paper by Dan Pelleg and Andrew Moore
*
* @param bestModel
* @return BIC of the given modell
*/
private double calcBIC(CentroidClusterModel bestModel) {
double loglike = 0;
int numCenters = bestModel.getNumberOfClusters();
int numDimensions = bestModel.getCentroidCoordinates(0).length;
int numParameters = numCenters - 1 + // probabilities
numCenters * numDimensions + // means
numCenters; // variance params
for (Cluster c : bestModel.getClusters()) {
int current_id = c.getClusterId();
loglike += logLikelihoodEstimate(c, bestModel.getCentroidCoordinates(current_id),
bestModel.getClusterAssignments(exampleSet), numCenters);
}
loglike -= numParameters / 2.0 * Math.log(examplesize);
return loglike;
}
示例2: createCentroidPlotter
import com.rapidminer.operator.clustering.CentroidClusterModel; //導入方法依賴的package包/類
private Plotter createCentroidPlotter(CentroidClusterModel cm, int width, int height) {
String[] dimensionNames = cm.getAttributeNames();
String[] columnNames = new String[dimensionNames.length + 1];
System.arraycopy(dimensionNames, 0, columnNames, 0, dimensionNames.length);
columnNames[columnNames.length - 1] = "Cluster";
SimpleDataTable dataTable = new SimpleDataTable("Centroid Positions", columnNames);
for (int i = 0; i < cm.getNumberOfClusters(); i++) {
double[] centroidValues = cm.getCentroidCoordinates(i);
String clusterName = cm.getCluster(i).getClusterId() + "";
double[] values = new double[centroidValues.length + 1];
System.arraycopy(centroidValues, 0, values, 0, centroidValues.length);
values[values.length - 1] = dataTable.mapString(values.length - 1, clusterName);
dataTable.add(new SimpleDataTableRow(values));
}
PlotterConfigurationModel settings = new PlotterConfigurationModel(PlotterConfigurationModel.PARALLEL_PLOT,
dataTable);
Plotter plotter = settings.getPlotter();
settings.setParameterAsString(PlotterAdapter.PARAMETER_PLOT_COLUMN, columnNames[columnNames.length - 1]);
settings.setParameterAsBoolean(LocalNormalizationPlotterAdapter.PARAMETER_LOCAL_NORMALIZATION, false);
settings.setParameterAsBoolean(LabelRotatingPlotterAdapter.PARAMETER_ROTATE_LABELS, true);
plotter.getPlotter().setSize(width, height);
return plotter;
}
示例3: calcBIC
import com.rapidminer.operator.clustering.CentroidClusterModel; //導入方法依賴的package包/類
/**
* Calculate the BIC like in the paper by Dan Pelleg and Andrew Moore
*
* @param bestModel
* @return BIC of the given modell
* @throws ProcessStoppedException
*/
private double calcBIC(CentroidClusterModel bestModel) throws ProcessStoppedException {
double loglike = 0;
int numCenters = bestModel.getNumberOfClusters();
int numDimensions = bestModel.getCentroidCoordinates(0).length;
int numParameters = numCenters - 1 + // probabilities
numCenters * numDimensions + // means
numCenters; // variance params
for (Cluster c : bestModel.getClusters()) {
int current_id = c.getClusterId();
loglike += logLikelihoodEstimate(c, bestModel.getCentroidCoordinates(current_id), numCenters);
}
loglike -= numParameters / 2.0 * Math.log(examplesize);
return loglike;
}
示例4: calcBIC
import com.rapidminer.operator.clustering.CentroidClusterModel; //導入方法依賴的package包/類
/**
* Calculate the BIC like in the paper by Dan Pelleg and Andrew Moore
*
* @param bestModel
* @return BIC of the given modell
*/
private double calcBIC(CentroidClusterModel bestModel) {
double loglike = 0;
int numCenters = bestModel.getNumberOfClusters();
int numDimensions = bestModel.getCentroidCoordinates(0).length;
int numParameters = (numCenters - 1) + // probabilities
numCenters * numDimensions + // means
numCenters; // variance params
for (Cluster c : bestModel.getClusters()) {
int current_id = c.getClusterId();
loglike += logLikelihoodEstimate(c,
bestModel.getCentroidCoordinates(current_id),
bestModel.getClusterAssignments(exampleSet), numCenters);
}
loglike -= (numParameters / 2.0) * Math.log(examplesize);
return loglike;
}
示例5: createCentroidPlotter
import com.rapidminer.operator.clustering.CentroidClusterModel; //導入方法依賴的package包/類
private Plotter createCentroidPlotter(CentroidClusterModel cm, int width, int height) {
String[] dimensionNames = cm.getAttributeNames();
String[] columnNames = new String[dimensionNames.length + 1];
System.arraycopy(dimensionNames, 0, columnNames, 0, dimensionNames.length);
columnNames[columnNames.length - 1] = "Cluster";
SimpleDataTable dataTable = new SimpleDataTable("Centroid Positions", columnNames);
for (int i = 0; i < cm.getNumberOfClusters(); i++) {
double[] centroidValues = cm.getCentroidCoordinates(i);
String clusterName = cm.getCluster(i).getClusterId() + "";
double[] values = new double[centroidValues.length + 1];
System.arraycopy(centroidValues, 0, values, 0, centroidValues.length);
values[values.length - 1] = dataTable.mapString(values.length - 1, clusterName);
dataTable.add(new SimpleDataTableRow(values));
}
PlotterConfigurationModel settings = new PlotterConfigurationModel(PlotterConfigurationModel.PARALLEL_PLOT, dataTable);
Plotter plotter = settings.getPlotter();
settings.setParameterAsString(ParallelPlotter2.PARAMETER_PLOT_COLUMN, columnNames[columnNames.length - 1]);
settings.setParameterAsBoolean(ParallelPlotter2.PARAMETER_LOCAL_NORMALIZATION, false);
settings.setParameterAsBoolean(ParallelPlotter2.PARAMETER_ROTATE_LABELS, true);
plotter.getPlotter().setSize(width, height);
return plotter;
}