/*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
/*
* HTML.java
* Copyright (C) 2009-2012 University of Waikato, Hamilton, New Zealand
*/
package weka.classifiers.evaluation.output.prediction;
import weka.classifiers.Classifier;
import weka.core.Instance;
import weka.core.Utils;
/**
<!-- globalinfo-start -->
* Outputs the predictions in HTML.
* <p/>
<!-- globalinfo-end -->
*
<!-- options-start -->
* Valid options are: <p/>
*
* <pre> -p <range>
* The range of attributes to print in addition to the classification.
* (default: none)</pre>
*
* <pre> -distribution
* Whether to turn on the output of the class distribution.
* Only for nominal class attributes.
* (default: off)</pre>
*
* <pre> -decimals <num>
* The number of digits after the decimal point.
* (default: 3)</pre>
*
* <pre> -file <path>
* The file to store the output in, instead of outputting it on stdout.
* Gets ignored if the supplied path is a directory.
* (default: .)</pre>
*
* <pre> -suppress
* In case the data gets stored in a file, then this flag can be used
* to suppress the regular output.
* (default: not suppressed)</pre>
*
<!-- options-end -->
*
* @author fracpete (fracpete at waikato dot ac dot nz)
* @version $Revision: 8937 $
*/
public class HTML
extends AbstractOutput {
/** for serialization. */
private static final long serialVersionUID = 7241252244954353300L;
/**
* Returns a string describing the output generator.
*
* @return a description suitable for
* displaying in the GUI
*/
public String globalInfo() {
return "Outputs the predictions in HTML.";
}
/**
* Returns a short display text, to be used in comboboxes.
*
* @return a short display text
*/
public String getDisplay() {
return "HTML";
}
/**
* Replaces certain characters with their HTML entities.
*
* @param s the string to process
* @return the processed string
*/
protected String sanitize(String s) {
String result;
result = s;
result = result.replaceAll("&", "&");
result = result.replaceAll("<", "<");
result = result.replaceAll(">", ">");
result = result.replaceAll("\"", """);
return result;
}
/**
* Performs the actual printing of the header.
*/
protected void doPrintHeader() {
append("<html>\n");
append("<head>\n");
append("<title>Predictions for dataset " + sanitize(m_Header.relationName()) + "</title>\n");
append("</head>\n");
append("<body>\n");
append("<div align=\"center\">\n");
append("<h3>Predictions for dataset " + sanitize(m_Header.relationName()) + "</h3>\n");
append("<table border=\"1\">\n");
append("<tr>\n");
if (m_Header.classAttribute().isNominal())
if (m_OutputDistribution)
append("<td>inst#</td><td>actual</td><td>predicted</td><td>error</td><td colspan=\"" + m_Header.classAttribute().numValues() + "\">distribution</td>");
else
append("<td>inst#</td><td>actual</td><td>predicted</td><td>error</td><td>prediction</td>");
else
append("<td>inst#</td><td>actual</td><td>predicted</td><td>error</td>");
if (m_Attributes != null) {
append("<td>");
boolean first = true;
for (int i = 0; i < m_Header.numAttributes(); i++) {
if (i == m_Header.classIndex())
continue;
if (m_Attributes.isInRange(i)) {
if (!first)
append("</td><td>");
append(sanitize(m_Header.attribute(i).name()));
first = false;
}
}
append("</td>");
}
append("</tr>\n");
}
/**
* Builds a string listing the attribute values in a specified range of indices,
* separated by commas and enclosed in brackets.
*
* @param instance the instance to print the values from
* @return a string listing values of the attributes in the range
*/
protected String attributeValuesString(Instance instance) {
StringBuffer text = new StringBuffer();
if (m_Attributes != null) {
boolean firstOutput = true;
m_Attributes.setUpper(instance.numAttributes() - 1);
for (int i=0; i<instance.numAttributes(); i++)
if (m_Attributes.isInRange(i) && i != instance.classIndex()) {
if (!firstOutput)
text.append("</td>");
if (m_Header.attribute(i).isNumeric())
text.append("<td align=\"right\">");
else
text.append("<td>");
text.append(sanitize(instance.toString(i)));
firstOutput = false;
}
if (!firstOutput)
text.append("</td>");
}
return text.toString();
}
protected void doPrintClassification(double[] dist, Instance inst, int index) throws Exception {
int prec = m_NumDecimals;
Instance withMissing = (Instance)inst.copy();
withMissing.setDataset(inst.dataset());
double predValue = 0;
if (Utils.sum(dist) == 0) {
predValue = Utils.missingValue();
} else {
if (inst.classAttribute().isNominal()) {
predValue = Utils.maxIndex(dist);
} else {
predValue = dist[0];
}
}
// index
append("<tr>");
append("<td>" + (index+1) + "</td>");
if (inst.dataset().classAttribute().isNumeric()) {
// actual
if (inst.classIsMissing())
append("<td align=\"right\">" + "?" + "</td>");
else
append("<td align=\"right\">" + Utils.doubleToString(inst.classValue(), prec) + "</td>");
// predicted
if (Utils.isMissingValue(predValue))
append("<td align=\"right\">" + "?" + "</td>");
else
append("<td align=\"right\">" + Utils.doubleToString(predValue, prec) + "</td>");
// error
if (Utils.isMissingValue(predValue) || inst.classIsMissing())
append("<td align=\"right\">" + "?" + "</td>");
else
append("<td align=\"right\">" + Utils.doubleToString(predValue - inst.classValue(), prec) + "</td>");
} else {
// actual
append("<td>" + ((int) inst.classValue()+1) + ":" + sanitize(inst.toString(inst.classIndex())) + "</td>");
// predicted
if (Utils.isMissingValue(predValue))
append("<td>" + "?" + "</td>");
else
append("<td>" + ((int) predValue+1) + ":" + sanitize(inst.dataset().classAttribute().value((int)predValue)) + "</td>");
// error?
if (!Utils.isMissingValue(predValue) && !inst.classIsMissing() && ((int) predValue+1 != (int) inst.classValue()+1))
append("<td>" + "+" + "</td>");
else
append("<td>" + " " + "</td>");
// prediction/distribution
if (m_OutputDistribution) {
if (Utils.isMissingValue(predValue)) {
append("<td>" + "?" + "</td>");
}
else {
append("<td align=\"right\">");
for (int n = 0; n < dist.length; n++) {
if (n > 0)
append("</td><td align=\"right\">");
if (n == (int) predValue)
append("*");
append(Utils.doubleToString(dist[n], prec));
}
append("</td>");
}
}
else {
if (Utils.isMissingValue(predValue))
append("<td align=\"right\">" + "?" + "</td>");
else
append("<td align=\"right\">" + Utils.doubleToString(dist[(int)predValue], prec) + "</td>");
}
}
// attributes
append(attributeValuesString(withMissing) + "</tr>\n");
}
/**
* Store the prediction made by the classifier as a string.
*
* @param classifier the classifier to use
* @param inst the instance to generate text from
* @param index the index in the dataset
* @throws Exception if something goes wrong
*/
protected void doPrintClassification(Classifier classifier, Instance inst, int index) throws Exception {
double[] d = classifier.distributionForInstance(inst);
doPrintClassification(d, inst, index);
}
/**
* Does nothing.
*/
protected void doPrintFooter() {
append("</table>\n");
append("</div>\n");
append("</body>\n");
append("</html>\n");
}
}