/*
* RapidMiner
*
* Copyright (C) 2001-2011 by Rapid-I and the contributors
*
* Complete list of developers available at our web site:
*
* http://rapid-i.com
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero 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 Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License
* along with this program. If not, see http://www.gnu.org/licenses/.
*/
package com.rapidminer.operator.generator;
import java.util.ArrayList;
import java.util.List;
import com.rapidminer.example.Attribute;
import com.rapidminer.example.Attributes;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.example.table.AttributeFactory;
import com.rapidminer.example.table.DoubleArrayDataRow;
import com.rapidminer.example.table.MemoryExampleTable;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.io.AbstractExampleSource;
import com.rapidminer.operator.ports.metadata.AttributeMetaData;
import com.rapidminer.operator.ports.metadata.ExampleSetMetaData;
import com.rapidminer.operator.ports.metadata.MetaData;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.parameter.ParameterTypeInt;
import com.rapidminer.tools.Ontology;
import com.rapidminer.tools.RandomGenerator;
import com.rapidminer.tools.math.container.Range;
/**
* Generates a random example set for testing purposes. The data represents a direct mailing
* example set.
*
* @author Ingo Mierswa
*/
public class DirectMailingExampleSetGenerator extends AbstractExampleSource {
/** The parameter name for "The number of generated examples." */
public static final String PARAMETER_NUMBER_EXAMPLES = "number_examples";
private static String[] ATTRIBUTE_NAMES = {
"name", "age", "lifestyle", "zip code", "family status", "car", "sports", "earnings"
};
private static int[] VALUE_TYPES = {
Ontology.NOMINAL,
Ontology.INTEGER,
Ontology.NOMINAL,
Ontology.INTEGER,
Ontology.NOMINAL,
Ontology.NOMINAL,
Ontology.NOMINAL,
Ontology.INTEGER
};
private static String[][] POSSIBLE_VALUES = {
null,
null,
{ "healthy", "active", "cozily" },
null,
{ "married", "single" },
{ "practical", "expensive" },
{ "soccer", "badminton", "athletics" },
null
};
public DirectMailingExampleSetGenerator(OperatorDescription description) {
super(description);
}
@Override
public ExampleSet createExampleSet() throws OperatorException {
// init
int numberOfExamples = getParameterAsInt(PARAMETER_NUMBER_EXAMPLES);
// create table
List<Attribute> attributes = new ArrayList<Attribute>();
for (int m = 0; m < ATTRIBUTE_NAMES.length; m++) {
Attribute current = AttributeFactory.createAttribute(ATTRIBUTE_NAMES[m], VALUE_TYPES[m]);
String[] possibleValues = POSSIBLE_VALUES[m];
if (possibleValues != null) {
for (int v = 0; v < possibleValues.length; v++)
current.getMapping().mapString(possibleValues[v]);
}
attributes.add(current);
}
Attribute label = AttributeFactory.createAttribute("label", Ontology.NOMINAL);
label.getMapping().mapString("no response");
label.getMapping().mapString("response");
attributes.add(label);
MemoryExampleTable table = new MemoryExampleTable(attributes);
// create data
RandomGenerator random = RandomGenerator.getRandomGenerator(this);
for (int n = 0; n < numberOfExamples; n++) {
double[] values = new double[ATTRIBUTE_NAMES.length + 1];
values[0] = attributes.get(0).getMapping().mapString(random.nextString(8));
// "name", "age", "lifestyle", "zip code", "family status", "car", "sports", "earnings"
values[1] = random.nextIntInRange(15, 70);
values[2] = random.nextInt(POSSIBLE_VALUES[2].length);
values[3] = random.nextIntInRange(10000, 100000);
values[4] = random.nextInt(POSSIBLE_VALUES[4].length);
values[5] = random.nextInt(POSSIBLE_VALUES[5].length);
values[6] = random.nextInt(POSSIBLE_VALUES[6].length);
values[7] = random.nextIntInRange(20000, 150000);
values[8] = label.getMapping().mapString("no response");
if (values[1] > 65) {
if (random.nextDouble() > 0.05)
values[8] = label.getMapping().mapString("response");
} else if (values[1] > 60) {
if (random.nextDouble() > 0.1)
values[8] = label.getMapping().mapString("response");
} else if (values[1] > 55) {
if (random.nextDouble() > 0.2)
values[8] = label.getMapping().mapString("response");
} else if (values[3] < 15000) {
if (random.nextDouble() > 0.1)
values[8] = label.getMapping().mapString("response");
} else if (values[7] > 140000) {
values[8] = label.getMapping().mapString("response");
}
table.addDataRow(new DoubleArrayDataRow(values));
}
// create example set and return it
return table.createExampleSet(label);
}
@Override
public List<ParameterType> getParameterTypes() {
List<ParameterType> types = super.getParameterTypes();
ParameterType type = new ParameterTypeInt(PARAMETER_NUMBER_EXAMPLES, "The number of generated examples.", 1, Integer.MAX_VALUE, 100);
type.setExpert(false);
types.add(type);
types.addAll(RandomGenerator.getRandomGeneratorParameters(this));
return types;
}
@Override
public MetaData getGeneratedMetaData() throws OperatorException {
ExampleSetMetaData emd = new ExampleSetMetaData();
emd.addAttribute(new AttributeMetaData("label", Attributes.LABEL_NAME, "response", "no response"));
emd.addAttribute(new AttributeMetaData("name", Ontology.NOMINAL));
// "name", "age", "lifestyle", "zip code", "family status", "car", "sports", "earnings"
emd.addAttribute(new AttributeMetaData("age", null, Ontology.INTEGER, new Range(15, 70)));
emd.addAttribute(new AttributeMetaData("lifestyle", null, POSSIBLE_VALUES[2]));
emd.addAttribute(new AttributeMetaData("zip code", null, Ontology.INTEGER, new Range(10000, 100000)));
emd.addAttribute(new AttributeMetaData("family status", null, POSSIBLE_VALUES[4]));
emd.addAttribute(new AttributeMetaData("car", null, POSSIBLE_VALUES[5]));
emd.addAttribute(new AttributeMetaData("sports", null, POSSIBLE_VALUES[6]));
emd.addAttribute(new AttributeMetaData("earnings", null, Ontology.INTEGER, new Range(20000, 150000)));
emd.setNumberOfExamples(getParameterAsInt(PARAMETER_NUMBER_EXAMPLES));
return emd;
}
}