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how to construct exampleSet

How do I construct a exampleSet instance from a data source?(either from a table or a tree model generated from data)

Thanks!

best
Happydust

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land

Hi,
do you mean by your own code? Then you could take a look at the "How to extend RapidMiner" tutorial available in our shop. It explains in detail how to create new ExampleSets.

Greetings,
Sebastian

Ghostrider

Here's some code from the RM Tutorial 4.6:


import com.rapidminer.example.*;
import com.rapidminer.example.table .*;
import com.rapidminer.example.set .*;
import com.rapidminer.tools .Ontology;
import java.util.*;

public class CreatingExampleTables {
	public static void main(String [] argv) {
		// create attribute list
		List <Attribute> attributes = new LinkedList<Attribute>();
		for ( int a = 0; a < getMyNumOfAttributes(); a++) {
			attributes.add( AttributeFactory . createAttribute (”att” + a,
			Ontology.REAL));
		}
		Attribute label = AttributeFactory . createAttribute (” label ”, Ontology.NOMINAL));
		attributes.add(label);
		//create table
		MemoryExampleTable table = new MemoryExampleTable(attributes);
		// fill table (here : only real values )
		for (int d = 0; d < getMyNumOfDataRows(); d++) {
			double[] data = new double[attributes.size()];
			for (int a = 0; a < getMyNumOfAttributes(); a++) {
				//fill with proper data here
				data = getMyValue(d, a);
			}
			// maps the nominal classification to a double value
			data[data.length - 1] = label.getMapping().mapString(getMyClassification(d));
			//add data row
			table.addDataRow(new DoubleArrayDataRow(data));
		}
		// create example set
		ExampleSet exampleSet = table.createExampleSet(label);
	}
}

haddock

Hi there,

A few weeks ago I posted a script to convert association rules to examples, but it has been removed, like a lot of my other posts, very, very, very annoying. Wessel had the same a while back, so at least it isn't personal. Anyways, here is the code, which shows that the 4.6 code for this is the same as the 5.0.

import com.rapidminer.tools.Ontology;

import com.rapidminer.operator.learner.associations.*;


AssociationRules rules = input[0];



// construct attribute set
Attribute[] attributes= new Attribute[11];
attributes[0] = AttributeFactory.createAttribute("Premise", Ontology.STRING);

attributes[1] = AttributeFactory.createAttribute("Premise Items", Ontology.INTEGER);
attributes[2] = AttributeFactory.createAttribute("Conclusion", Ontology.STRING);
attributes[3] = AttributeFactory.createAttribute("Conclusion Items", Ontology.INTEGER);
attributes[4] = AttributeFactory.createAttribute("Confidence", Ontology.REAL);
attributes[5] = AttributeFactory.createAttribute("Conviction", Ontology.REAL);
attributes[6] = AttributeFactory.createAttribute("Gain", Ontology.REAL);
attributes[7] = AttributeFactory.createAttribute("Laplace", Ontology.REAL);

attributes[8] = AttributeFactory.createAttribute("Lift", Ontology.REAL);
attributes[9] = AttributeFactory.createAttribute("Ps", Ontology.REAL);


attributes[10] = AttributeFactory.createAttribute("Total Support", Ontology.REAL);



MemoryExampleTable table = new MemoryExampleTable(attributes);
DataRowFactory ROW_FACTORY = new DataRowFactory(0);

String[] strings= new String[11];

for (AssociationRule rule : rules) {
		// construct example data
        strings[0]=rule.toPremiseString();
        strings[1]=rule.premise.size().toString();
        strings[2]=rule.toConclusionString();
        strings[3]=rule.conclusion.size().toString();
        strings[4]=rule.getConfidence().toString();
        strings[5]=rule.getConviction().toString();
        strings[6]=rule.getGain().toString();
        strings[7]=rule.getLaplace().toString();
        strings[8]=rule.getLift().toString();

        strings[9]=rule.getPs().toString();
        strings[10]=rule.getTotalSupport().toString();

        // make and add row
        DataRow row = ROW_FACTORY.create(strings, attributes); 
        table.addDataRow(row);	
		}

ExampleSet exampleSet = table.createExampleSet();
return exampleSet;

fischer

Hi Haddock and wessel,

what post are you referring to that was deleted? The only posts we delete are spam posts, and we did that with a few posts that were posted recently. Wessel was one of the reporters, I believe. Maybe we deleted the entire thread rather than only the spam post. I apologize if that happened, it was definitely nothing personal :-)

Cheers,
Simon