@Override
public String toString() {
updateDistributionProperties();
return ("Normal distribution --> mean: "
+ Tools.formatNumber(mean)
+ ", standard deviation: "
+ Tools.formatNumber(standardDeviation));
}
public String toString() {
return "ANOVA result (f="
+ Tools.formatNumber(fValue)
+ ", prob="
+ Tools.formatNumber(prob)
+ ", alpha="
+ Tools.formatNumber(alpha)
+ ")";
}
public Object getValueAt(int row, int col) {
if (col == 0) {
return matrix.getAnovaAttributeNames().get(row);
} else {
return Tools.formatNumber(matrix.getProbabilities()[row][col - 1]);
}
}
@Override
public String toResultString() {
StringBuilder result =
new StringBuilder(
Tools.getLineSeparator() + "Principal Components:" + Tools.getLineSeparator());
if (manualNumber) {
result.append("Number of Components: " + numberOfComponents + Tools.getLineSeparator());
} else {
result.append("Proportion Threshold: " + proportionThreshold + Tools.getLineSeparator());
}
for (int i = 0; i < vMatrix.getColumnDimension(); i++) {
result.append("PC " + (i + 1) + ": ");
for (int j = 0; j < attributeNames.length; j++) {
double value = vMatrix.get(i, j);
if (value > 0) {
result.append(" + ");
} else {
result.append(" - ");
}
result.append(Tools.formatNumber(Math.abs(value)) + " * " + attributeNames[j]);
}
result.append(Tools.getLineSeparator());
}
return result.toString();
}
@Override
public List<String> getModelNames() {
List<String> names = new LinkedList<String>();
for (int i = 0; i < this.getNumberOfModels(); i++) {
names.add("Model " + (i + 1) + " [w = " + Tools.formatNumber(getWeightForModel(i)) + "]");
}
return names;
}
@Override
public String toString() {
String results = new String();
for (int i = 0; i < names.size(); i++) {
results +=
names.get(i).toString() + ": " + Tools.formatNumber(values.get(i).doubleValue()) + "\n";
}
return results;
// return name+" "+ Tools.formatNumber(value);
}
@Override
public Component getVisualizationComponent(Object renderable, IOContainer ioContainer) {
TTestSignificanceTestResult result = (TTestSignificanceTestResult) renderable;
PerformanceVector[] allVectors = result.getAllVectors();
StringBuffer buffer = new StringBuffer();
Color bgColor = SwingTools.LIGHTEST_YELLOW;
String bgColorString =
Integer.toHexString(bgColor.getRed())
+ Integer.toHexString(bgColor.getGreen())
+ Integer.toHexString(bgColor.getBlue());
buffer.append("<table bgcolor=\"" + bgColorString + "\" border=\"1\">");
buffer.append("<tr><td></td>");
for (int i = 0; i < result.getAllVectors().length; i++) {
buffer.append(
"<td>"
+ Tools.formatNumber(allVectors[i].getMainCriterion().getAverage())
+ " +/- "
+ Tools.formatNumber(Math.sqrt(allVectors[i].getMainCriterion().getVariance()))
+ "</td>");
}
buffer.append("</tr>");
for (int i = 0; i < allVectors.length; i++) {
buffer.append(
"<tr><td>"
+ Tools.formatNumber(allVectors[i].getMainCriterion().getAverage())
+ " +/- "
+ Tools.formatNumber(Math.sqrt(allVectors[i].getMainCriterion().getVariance()))
+ "</td>");
for (int j = 0; j < allVectors.length; j++) {
buffer.append("<td>");
if (!Double.isNaN(result.getProbMatrix()[i][j])) {
double prob = result.getProbMatrix()[i][j];
if (prob < result.getAlpha()) {
buffer.append("<b>");
}
buffer.append(Tools.formatNumber(prob));
if (prob < result.getAlpha()) {
buffer.append("</b>");
}
}
buffer.append("</td>");
}
buffer.append("</tr>");
}
buffer.append("</table>");
buffer.append(
"<br>Probabilities for random values with the same result.<br>Bold values are smaller than alpha="
+ Tools.formatNumber(result.getAlpha())
+ " which indicates a probably significant difference between the actual mean values!");
JEditorPane textPane =
new ExtendedHTMLJEditorPane(
"text/html", "<html><h1>" + getName() + "</h1>" + buffer.toString() + "</html>");
textPane.setBackground((new JLabel()).getBackground());
textPane.setBorder(javax.swing.BorderFactory.createEmptyBorder(11, 11, 11, 11));
textPane.setEditable(false);
return new ExtendedJScrollPane(textPane);
}
public static int fillDataTable(
SimpleDataTable dataTable,
Map<String, double[]> lastPopulation,
Population pop,
boolean drawDominated) {
lastPopulation.clear();
dataTable.clear();
int numberOfCriteria = 0;
for (int i = 0; i < pop.getNumberOfIndividuals(); i++) {
boolean dominated = false;
if (!drawDominated) {
for (int j = 0; j < pop.getNumberOfIndividuals(); j++) {
if (i == j) continue;
if (NonDominatedSortingSelection.isDominated(pop.get(i), pop.get(j))) {
dominated = true;
break;
}
}
}
if (drawDominated || (!dominated)) {
StringBuffer id = new StringBuffer(i + " (");
PerformanceVector current = pop.get(i).getPerformance();
numberOfCriteria = Math.max(numberOfCriteria, current.getSize());
double[] data = new double[current.getSize()];
for (int d = 0; d < data.length; d++) {
data[d] = current.getCriterion(d).getFitness();
if (d != 0) id.append(", ");
id.append(Tools.formatNumber(data[d]));
}
id.append(")");
dataTable.add(new SimpleDataTableRow(data, id.toString()));
double[] weights = pop.get(i).getWeights();
double[] clone = new double[weights.length];
System.arraycopy(weights, 0, clone, 0, weights.length);
lastPopulation.put(id.toString(), clone);
}
}
return numberOfCriteria;
}
@Override
public String toString() {
StringBuffer distributionDescription = new StringBuffer();
boolean first = true;
for (int i = 0; i < valueNames.length; i++) {
if (!first) {
distributionDescription.append("\t");
}
distributionDescription.append(valueNames[i]);
first = false;
}
first = true;
distributionDescription.append(Tools.getLineSeparator());
for (int i = 0; i < valueNames.length; i++) {
if (!first) {
distributionDescription.append("\t");
}
distributionDescription.append(Tools.formatNumber(probabilities[i]));
first = false;
}
return distributionDescription.toString();
}
public ANOVAMatrixViewer(ANOVAMatrix matrix) {
super(new BorderLayout());
JPanel infoPanel = new JPanel(new FlowLayout(FlowLayout.LEFT));
// info string
JTextPane infoText = new JTextPane();
infoText.setEditable(false);
infoText.setBackground(infoPanel.getBackground());
infoText.setFont(infoText.getFont().deriveFont(Font.BOLD));
infoText.setText(
"A dark background indicates that the probability for non-difference between the groups is less than "
+ Tools.formatNumber(matrix.getSignificanceLevel()));
infoPanel.add(infoText);
infoPanel.setBorder(BorderFactory.createEtchedBorder());
add(infoPanel, BorderLayout.NORTH);
// table
ANOVAMatrixViewerTable table = new ANOVAMatrixViewerTable(matrix);
table.setBorder(BorderFactory.createEtchedBorder());
add(new ExtendedJScrollPane(table), BorderLayout.CENTER);
}
@Override
public String toResultString() {
StringBuilder result =
new StringBuilder(
Tools.getLineSeparator() + "Principal Components:" + Tools.getLineSeparator());
if (manualNumber) {
result.append("Number of Components: " + numberOfComponents + Tools.getLineSeparator());
} else {
result.append("Variance Threshold: " + varianceThreshold + Tools.getLineSeparator());
}
for (int i = 0; i < eigenVectors.size(); i++) {
result.append("PC " + (i + 1) + ": ");
for (int j = 0; j < attributeNames.length; j++) {
double value = eigenVectors.get(i).getEigenvector()[j];
if (value > 0) result.append(" + ");
else result.append(" - ");
result.append(Tools.formatNumber(Math.abs(value)) + " * " + attributeNames[j]);
}
result.append(Tools.getLineSeparator());
}
return result.toString();
}
/** @return a <code>String</code> representation of this boosting model. */
@Override
public String toString() {
StringBuffer result =
new StringBuffer(
super.toString()
+ Tools.getLineSeparator()
+ "Number of inner models: "
+ this.getNumberOfModels()
+ Tools.getLineSeparators(2));
for (int i = 0; i < this.getNumberOfModels(); i++) {
Model model = this.getModel(i);
result.append(
(i > 0 ? Tools.getLineSeparator() : "")
+ "Embedded model #"
+ i
+ " (weight: "
+ Tools.formatNumber(this.getWeightForModel(i))
+ "): "
+ Tools.getLineSeparator()
+ model.toResultString());
}
return result.toString();
}
/** Returns a label that displays the {@link #toResultString()} result encoded as html. */
public java.awt.Component getVisualizationComponent(IOContainer container) {
StringBuffer buffer = new StringBuffer();
Color bgColor = SwingTools.LIGHTEST_YELLOW;
String bgColorString =
"#"
+ Integer.toHexString(bgColor.getRed())
+ Integer.toHexString(bgColor.getGreen())
+ Integer.toHexString(bgColor.getBlue());
Color headerColor = SwingTools.LIGHTEST_BLUE;
String headerColorString =
"#"
+ Integer.toHexString(headerColor.getRed())
+ Integer.toHexString(headerColor.getGreen())
+ Integer.toHexString(headerColor.getBlue());
buffer.append("<table bgcolor=\"" + bgColorString + "\" border=\"1\">");
buffer.append(
"<tr bgcolor=\""
+ headerColorString
+ "\"><th>Source</th><th>Square Sums</th><th>DF</th><th>Mean Squares</th><th>F</th><th>Prob</th></tr>");
buffer.append(
"<tr><td>Between</td><td>"
+ Tools.formatNumber(sumSquaresBetween)
+ "</td><td>"
+ df1
+ "</td><td>"
+ Tools.formatNumber(meanSquaresBetween)
+ "</td><td>"
+ Tools.formatNumber(fValue)
+ "</td><td>"
+ Tools.formatNumber(prob)
+ "</td></tr>");
buffer.append(
"<tr><td>Residuals</td><td>"
+ Tools.formatNumber(sumSquaresResiduals)
+ "</td><td>"
+ df2
+ "</td><td>"
+ Tools.formatNumber(meanSquaresResiduals)
+ "</td><td></td><td></td></tr>");
buffer.append(
"<tr><td>Total</td><td>"
+ Tools.formatNumber(sumSquaresBetween + sumSquaresResiduals)
+ "</td><td>"
+ (df1 + df2)
+ "</td><td></td><td></td><td></td></tr>");
buffer.append("</table>");
buffer.append(
"<br>Probability for random values with the same result: "
+ Tools.formatNumber(prob)
+ "<br>");
if (prob < alpha)
buffer.append(
"Difference between actual mean values is probably significant, since "
+ Tools.formatNumber(prob)
+ " < alpha = "
+ Tools.formatNumber(alpha)
+ "!");
else
buffer.append(
"Difference between actual mean values is probably not significant, since "
+ Tools.formatNumber(prob)
+ " > alpha = "
+ Tools.formatNumber(alpha)
+ "!");
JEditorPane textPane =
new JEditorPane(
"text/html", "<html><h1>" + getName() + "</h1>" + buffer.toString() + "</html>");
textPane.setBackground((new JLabel()).getBackground());
textPane.setBorder(javax.swing.BorderFactory.createEmptyBorder(11, 11, 11, 11));
return new ExtendedJScrollPane(textPane);
}
private void addRuleNodes(boolean[] filter) {
Iterator<String> e = edgeList.iterator();
while (e.hasNext()) {
graph.removeEdge(e.next());
}
Iterator<String> n = nodeList.iterator();
while (n.hasNext()) {
graph.removeVertex(n.next());
}
edgeList.clear();
nodeList.clear();
toolTipInfos.clear();
asPremise.clear();
asConclusion.clear();
int ruleIndex = 1;
for (int r = 0; r < rules.getNumberOfRules(); r++) {
if (filter[r]) {
AssociationRule rule = rules.getRule(r);
// define conjunction node
String conjunctionNode =
"Rule "
+ ruleIndex
+ " ("
+ Tools.formatNumber(rule.getTotalSupport())
+ " / "
+ Tools.formatNumber(rule.getConfidence())
+ ")";
toolTipInfos.put(
conjunctionNode,
"<html><b>Rule "
+ ruleIndex
+ "</b><br>"
+ SwingTools.addLinebreaks(
rule.toPremiseString() + " --> " + rule.toConclusionString())
+ "<br><b>Support:</b> "
+ rule.getTotalSupport()
+ "<br><b>Confidence:</b> "
+ rule.getConfidence()
+ "<br><b>Lift:</b> "
+ rule.getLift()
+ "<br><b>Gain:</b> "
+ rule.getGain()
+ "<br><b>Conviction:</b> "
+ rule.getConviction()
+ "<br><b>Laplace:</b> "
+ rule.getLaplace()
+ "<br><b>Ps:</b> "
+ rule.getPs()
+ "</html>");
nodeList.add(conjunctionNode);
// add premise nodes
Iterator<Item> p = rule.getPremiseItems();
while (p.hasNext()) {
Item premiseItem = p.next();
String edgeId = edgeFactory.create();
edgeList.add(edgeId);
nodeList.add(premiseItem.toString());
graph.addEdge(edgeId, premiseItem.toString(), conjunctionNode);
List<String> premiseList = asPremise.get(premiseItem.toString());
if (premiseList == null) {
premiseList = new LinkedList<String>();
asPremise.put(premiseItem.toString(), premiseList);
}
premiseList.add("Rule " + ruleIndex);
}
// add conclusion nodes
Iterator<Item> c = rule.getConclusionItems();
while (c.hasNext()) {
Item conclusionItem = c.next();
String edgeId = edgeFactory.create();
edgeList.add(edgeId);
nodeList.add(conclusionItem.toString());
graph.addEdge(edgeId, conjunctionNode, conclusionItem.toString());
List<String> conclusionList = asConclusion.get(conclusionItem.toString());
if (conclusionList == null) {
conclusionList = new LinkedList<String>();
asConclusion.put(conclusionItem.toString(), conclusionList);
}
conclusionList.add("Rule " + ruleIndex);
}
}
ruleIndex++;
}
}
@Override
public String toString() {
return "Relative neighborhood with a fraction of "
+ Tools.formatNumber(relativeSize, 3)
+ " of the complete data set";
}
