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The Waikato Environment for Knowledge Analysis (WEKA), a machine
learning workbench. This version represents the developer version, the
"bleeding edge" of development, you could say. New functionality gets added
to this version.
/*
* 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
*
* The following DTD is used:
*
* <!DOCTYPE predictions
* [
* <!ELEMENT predictions (prediction*)>
* <!ATTLIST predictions version CDATA "3.5.8">
* <!ATTLIST predictions name CDATA #REQUIRED>
*
* <!ELEMENT prediction ((actual_label,predicted_label,error,(prediction|distribution),attributes?)|(actual_value,predicted_value,error,attributes?))>
* <!ATTLIST prediction index CDATA #REQUIRED>
*
* <!ELEMENT actual_label ANY>
* <!ATTLIST actual_label index CDATA #REQUIRED>
* <!ELEMENT predicted_label ANY>
* <!ATTLIST predicted_label index CDATA #REQUIRED>
* <!ELEMENT error ANY>
* <!ELEMENT prediction ANY>
* <!ELEMENT distribution (class_label+)>
* <!ELEMENT class_label ANY>
* <!ATTLIST class_label index CDATA #REQUIRED>
* <!ATTLIST class_label predicted (yes|no) "no">
* <!ELEMENT actual_value ANY>
* <!ELEMENT predicted_value ANY>
* <!ELEMENT attributes (attribute+)>
* <!ELEMENT attribute ANY>
* <!ATTLIST attribute index CDATA #REQUIRED>
* <!ATTLIST attribute name CDATA #REQUIRED>
* <!ATTLIST attribute type (numeric|date|nominal|string|relational) #REQUIRED>
* ]
* >
*
*
* Valid options are:
*
* -p <range>
* The range of attributes to print in addition to the classification.
* (default: none)
*
* -distribution
* Whether to turn on the output of the class distribution.
* Only for nominal class attributes.
* (default: off)
*
* -decimals <num>
* The number of digits after the decimal point.
* (default: 3)
*
* -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: .)
*
* -suppress
* In case the data gets stored in a file, then this flag can be used
* to suppress the regular output.
* (default: not suppressed)
*
*
* @author fracpete (fracpete at waikato dot ac dot nz)
* @version $Revision: 8937 $
*/
public class XML
extends AbstractOutput {
/** for serialization. */
private static final long serialVersionUID = -3165514277316824801L;
/** the DocType definition. */
public final static String DTD_DOCTYPE = XMLDocument.DTD_DOCTYPE;
/** the Element definition. */
public final static String DTD_ELEMENT = XMLDocument.DTD_ELEMENT;
/** the AttList definition. */
public final static String DTD_ATTLIST = XMLDocument.DTD_ATTLIST;
/** the optional marker. */
public final static String DTD_OPTIONAL = XMLDocument.DTD_OPTIONAL;
/** the at least one marker. */
public final static String DTD_AT_LEAST_ONE = XMLDocument.DTD_AT_LEAST_ONE;
/** the zero or more marker. */
public final static String DTD_ZERO_OR_MORE = XMLDocument.DTD_ZERO_OR_MORE;
/** the option separator. */
public final static String DTD_SEPARATOR = XMLDocument.DTD_SEPARATOR;
/** the CDATA placeholder. */
public final static String DTD_CDATA = XMLDocument.DTD_CDATA;
/** the ANY placeholder. */
public final static String DTD_ANY = XMLDocument.DTD_ANY;
/** the #PCDATA placeholder. */
public final static String DTD_PCDATA = XMLDocument.DTD_PCDATA;
/** the #IMPLIED placeholder. */
public final static String DTD_IMPLIED = XMLDocument.DTD_IMPLIED;
/** the #REQUIRED placeholder. */
public final static String DTD_REQUIRED = XMLDocument.DTD_REQUIRED;
/** the "version" attribute. */
public final static String ATT_VERSION = XMLDocument.ATT_VERSION;
/** the "name" attribute. */
public final static String ATT_NAME = XMLDocument.ATT_NAME;
/** the "type" attribute. */
public final static String ATT_TYPE = "type";
/** the value "yes". */
public final static String VAL_YES = XMLDocument.VAL_YES;
/** the value "no". */
public final static String VAL_NO = XMLDocument.VAL_NO;
/** the predictions tag. */
public final static String TAG_PREDICTIONS = "predictions";
/** the prediction tag. */
public final static String TAG_PREDICTION = "prediction";
/** the actual_nominal tag. */
public final static String TAG_ACTUAL_LABEL = "actual_label";
/** the predicted_nominal tag. */
public final static String TAG_PREDICTED_LABEL = "predicted_label";
/** the error tag. */
public final static String TAG_ERROR = "error";
/** the distribution tag. */
public final static String TAG_DISTRIBUTION = "distribution";
/** the class_label tag. */
public final static String TAG_CLASS_LABEL = "class_label";
/** the actual_numeric tag. */
public final static String TAG_ACTUAL_VALUE = "actual_value";
/** the predicted_numeric tag. */
public final static String TAG_PREDICTED_VALUE = "predicted_value";
/** the attributes tag. */
public final static String TAG_ATTRIBUTES = "attributes";
/** the attribute tag. */
public final static String TAG_ATTRIBUTE = "attribute";
/** the index attribute. */
public final static String ATT_INDEX = "index";
/** the predicted attribute. */
public final static String ATT_PREDICTED = "predicted";
/** the DTD. */
public final static String DTD =
"\n"
+ " \n"
+ " \n"
+ "\n"
+ " \n"
+ " \n"
+ "\n"
+ " \n"
+ " \n"
+ " \n"
+ " \n"
+ " \n"
+ " \n"
+ " \n"
+ " \n"
+ " \n"
+ " \n"
+ " \n"
+ " \n"
+ " \n"
+ " \n"
+ " \n"
+ " \n"
+ " \n"
+ "]\n"
+ ">";
/**
* Returns a string describing the output generator.
*
* @return a description suitable for
* displaying in the GUI
*/
public String globalInfo() {
return
"Outputs the predictions in XML.\n\n"
+ "The following DTD is used:\n\n"
+ DTD;
}
/**
* Returns a short display text, to be used in comboboxes.
*
* @return a short display text
*/
public String getDisplay() {
return "XML";
}
/**
* Replaces certain characters with their XML 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("\n");
append("\n");
append(DTD + "\n\n");
append("<" + TAG_PREDICTIONS + " " + ATT_VERSION + "=\"" + Version.VERSION + "\"" + " " + ATT_NAME + "=\"" + sanitize(m_Header.relationName()) + "\">\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) {
text.append(" <" + TAG_ATTRIBUTES + ">\n");
m_Attributes.setUpper(instance.numAttributes() - 1);
for (int i=0; i");
text.append(sanitize(instance.toString(i)));
text.append("\n");
}
}
text.append(" \n");
}
return text.toString();
}
/**
* Store the prediction made by the classifier as a string.
*
* @param dist the distribution 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(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];
}
}
// opening tag
append(" <" + TAG_PREDICTION + " " + ATT_INDEX + "=\"" + (index+1) + "\">\n");
if (inst.dataset().classAttribute().isNumeric()) {
// actual
append(" <" + TAG_ACTUAL_VALUE + ">");
if (inst.classIsMissing())
append("?");
else
append(Utils.doubleToString(inst.classValue(), prec));
append("\n");
// predicted
append(" <" + TAG_PREDICTED_VALUE + ">");
if (inst.classIsMissing())
append("?");
else
append(Utils.doubleToString(predValue, prec));
append("\n");
// error
append(" <" + TAG_ERROR + ">");
if (Utils.isMissingValue(predValue) || inst.classIsMissing())
append("?");
else
append(Utils.doubleToString(predValue - inst.classValue(), prec));
append("\n");
} else {
// actual
append(" <" + TAG_ACTUAL_LABEL + " " + ATT_INDEX + "=\"" + ((int) inst.classValue()+1) + "\"" + ">");
append(sanitize(inst.toString(inst.classIndex())));
append("\n");
// predicted
append(" <" + TAG_PREDICTED_LABEL + " " + ATT_INDEX + "=\"" + ((int) predValue+1) + "\"" + ">");
if (Utils.isMissingValue(predValue))
append("?");
else
append(sanitize(inst.dataset().classAttribute().value((int)predValue)));
append("\n");
// error?
append(" <" + TAG_ERROR + ">");
if (!Utils.isMissingValue(predValue) && !inst.classIsMissing() && ((int) predValue+1 != (int) inst.classValue()+1))
append(VAL_YES);
else
append(VAL_NO);
append("\n");
// prediction/distribution
if (m_OutputDistribution) {
append(" <" + TAG_DISTRIBUTION + ">\n");
for (int n = 0; n < dist.length; n++) {
append(" <" + TAG_CLASS_LABEL + " " + ATT_INDEX + "=\"" + (n+1) + "\"");
if (!Utils.isMissingValue(predValue) && (n == (int) predValue))
append(" " + ATT_PREDICTED + "=\"" + VAL_YES + "\"");
append(">");
append(Utils.doubleToString(dist[n], prec));
append("\n");
}
append(" \n");
}
else {
append(" <" + TAG_PREDICTION + ">");
if (Utils.isMissingValue(predValue))
append("?");
else
append(Utils.doubleToString(dist[(int)predValue], prec));
append("\n");
}
}
// attributes
if (m_Attributes != null)
append(attributeValuesString(withMissing));
// closing tag
append(" \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("\n");
}
}