/**
* Copyright (C) 2001-2017 by RapidMiner and the contributors
*
* Complete list of developers available at our web site:
*
* http://rapidminer.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.utils.ExampleSetBuilder;
import com.rapidminer.example.utils.ExampleSets;
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 team profit example
* set.
*
* @author Ingo Mierswa
*/
public class TeamProfitExampleSetGenerator 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 = { "size", "leader", "number of qualified employees", "leader changed",
"average years of experience", "structure" };
private static int[] VALUE_TYPES = { Ontology.INTEGER, Ontology.NOMINAL, Ontology.INTEGER, Ontology.BINOMINAL,
Ontology.INTEGER, Ontology.BINOMINAL };
private static String[][] POSSIBLE_VALUES = { null,
{ "Mr. Brown", "Mr. Miller", "Mrs. Smith", "Mrs. Hanson", "Mrs. Green", "Mr. Chang" }, null, { "yes", "no" },
null, { "flat", "hierachical" } };
public TeamProfitExampleSetGenerator(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>();
Attribute id = AttributeFactory.createAttribute("teamID", Ontology.NOMINAL);
attributes.add(id);
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.BINOMINAL);
label.getMapping().mapString("good");
label.getMapping().mapString("bad");
attributes.add(label);
ExampleSetBuilder builder = ExampleSets.from(attributes).withExpectedSize(numberOfExamples);
// create data
RandomGenerator random = RandomGenerator.getRandomGenerator(this);
// init operator progress
getProgress().setTotal(numberOfExamples);
for (int n = 0; n < numberOfExamples; n++) {
double[] values = new double[ATTRIBUTE_NAMES.length + 2];
values[0] = attributes.get(0).getMapping().mapString("team_" + n);
// "size", "leader", "number of qualified employees", "leader changed",
// "average years of experience", "structure"
values[1] = random.nextIntInRange(5, 20);
values[2] = random.nextInt(POSSIBLE_VALUES[1].length);
values[3] = Math.round(random.nextDouble() * (values[1] - 1) + 1);
values[4] = random.nextInt(POSSIBLE_VALUES[3].length);
values[5] = random.nextIntInRange(1, 10);
values[6] = random.nextInt(POSSIBLE_VALUES[5].length);
values[7] = label.getMapping().mapString("bad");
if (values[1] > 18) {
if (random.nextDouble() > 0.05) {
values[7] = label.getMapping().mapString("good");
}
} else if (values[1] > 15) {
if (random.nextDouble() > 0.1) {
values[7] = label.getMapping().mapString("good");
}
} else if (values[4] == 1) {
if (random.nextDouble() > 0.1) {
values[7] = label.getMapping().mapString("good");
}
}
builder.addRow(values);
getProgress().step();
}
getProgress().complete();
// create example set and return it
return builder.withRole(label, Attributes.LABEL_NAME).build();
}
@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, "good", "bad"));
emd.addAttribute(new AttributeMetaData("teamID", Ontology.NOMINAL));
// "size", "leader", "number of qualified employees", "leader changed",
// "average years of experience", "structure"
emd.addAttribute(new AttributeMetaData("size", null, Ontology.INTEGER, new Range(5, 20)));
emd.addAttribute(new AttributeMetaData("leader", null, POSSIBLE_VALUES[1]));
emd.addAttribute(new AttributeMetaData("number of qualified employees", null, Ontology.INTEGER, new Range(1, 10)));
emd.addAttribute(new AttributeMetaData("leader changed", null, POSSIBLE_VALUES[3]));
emd.addAttribute(new AttributeMetaData("average years of experience", null, Ontology.INTEGER, new Range(1, 10)));
emd.addAttribute(new AttributeMetaData("structure", null, POSSIBLE_VALUES[5]));
emd.setNumberOfExamples(getParameterAsInt(PARAMETER_NUMBER_EXAMPLES));
return emd;
}
}