How to use
pad
method
in
weka.clusterers.EM

Best Java code snippets using weka.clusterers.EM.pad (Showing top 2 results out of 315)

temp.append(pad("Cluster", " ",
 (maxAttWidth + maxWidth + 1) - "Cluster".length(), true));
.append(pad("Attribute", " ", maxAttWidth - "Attribute".length(), false));
 temp.append(pad(classL, " ", maxWidth + 1 - classL.length(), true));
temp.append(pad("", " ", maxAttWidth, true));
for (int i = 0; i < m_num_clusters; i++) {
 String priorP = Utils.doubleToString(m_priors[i], maxWidth, 2).trim();
 priorP = "(" + priorP + ")";
 temp.append(pad(priorP, " ", maxWidth + 1 - priorP.length(), true));
temp.append(pad("", "=", maxAttWidth + (maxWidth * m_num_clusters)
 + m_num_clusters + 1, true));
temp.append("\n");
  temp.append(pad(meanL, " ", maxAttWidth + 1 - meanL.length(), false));
  for (int j = 0; j < m_num_clusters; j++) {
   temp.append(pad(mean, " ", maxWidth + 1 - mean.length(), true));
  .append(pad(stdDevL, " ", maxAttWidth + 1 - stdDevL.length(), false));
  for (int j = 0; j < m_num_clusters; j++) {
   String stdDev = Utils.doubleToString(m_modelNormal[j][i][1],
    maxWidth, 4).trim();
   temp.append(pad(stdDev, " ", maxWidth + 1 - stdDev.length(), true));
  for (int j = 0; j < a.numValues(); j++) {

temp.append(pad("Cluster", " ",
 (maxAttWidth + maxWidth + 1) - "Cluster".length(), true));
.append(pad("Attribute", " ", maxAttWidth - "Attribute".length(), false));
 temp.append(pad(classL, " ", maxWidth + 1 - classL.length(), true));
temp.append(pad("", " ", maxAttWidth, true));
for (int i = 0; i < m_num_clusters; i++) {
 String priorP = Utils.doubleToString(m_priors[i], maxWidth, 2).trim();
 priorP = "(" + priorP + ")";
 temp.append(pad(priorP, " ", maxWidth + 1 - priorP.length(), true));
temp.append(pad("", "=", maxAttWidth + (maxWidth * m_num_clusters)
 + m_num_clusters + 1, true));
temp.append("\n");
  temp.append(pad(meanL, " ", maxAttWidth + 1 - meanL.length(), false));
  for (int j = 0; j < m_num_clusters; j++) {
   temp.append(pad(mean, " ", maxWidth + 1 - mean.length(), true));
  .append(pad(stdDevL, " ", maxAttWidth + 1 - stdDevL.length(), false));
  for (int j = 0; j < m_num_clusters; j++) {
   String stdDev = Utils.doubleToString(m_modelNormal[j][i][1],
    maxWidth, 4).trim();
   temp.append(pad(stdDev, " ", maxWidth + 1 - stdDev.length(), true));
  for (int j = 0; j < a.numValues(); j++) {

Popular methods of EM

<init>
Constructor.
setNumClusters
Set the number of clusters (-1 to select by CV).
CVClusters
estimate the number of clusters by cross validation on the training data.
E
The E step of the EM algorithm. Estimate cluster membership probabilities.
EM_Init
Initialize the global aggregated estimators and storage.
EM_Report
verbose output for debugging
M
The M step of the EM algorithm.
M_reEstimate
buildClusterer
Generates a clusterer. Has to initialize all fields of the clusterer that are not being set via opti
distributionForInstance
doEM
Perform the EM algorithm
estimate_priors
calculate prior probabilites for the clusters

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How to use padmethodin weka.clusterers.EM

Best Java code snippets using weka.clusterers.EM.pad (Showing top 2 results out of 315)

How to use
pad
method
in
weka.clusterers.EM