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Massive On-line Analysis is an environment for massive data mining. MOA provides a framework for data stream mining and includes tools for evaluation and a collection of machine learning algorithms. Related to the WEKA project, also written in Java, while scaling to more demanding problems.

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/*
 *    DataObject.java
 *
 *    @author F. Sanchez, I. Assent, P. Kranen, C. Baldauf, T. Seidl
 *    @author G. Piskas, A. Gounaris
 * 
 *    Licensed under the Apache License, Version 2.0 (the "License");
 *    you may not use this file except in compliance with the License.
 *    You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 *    Unless required by applicable law or agreed to in writing, software
 *    distributed under the License is distributed on an "AS IS" BASIS,
 *    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *    See the License for the specific language governing permissions and
 *    limitations under the License.
 *    
 *    
 */

package moa.clusterers.outliers.AnyOut.util;

import com.yahoo.labs.samoa.instances.Instance;



/**
 * This object encapsulates a data point.
 * @author Fernando Sanchez Villaamil
 */

public class DataObject {
    
    private int id;
    private Instance inst;
    private double[] features;
    private int classLabel;
    private boolean isOutiler;

    /**
     * Returns the features (label attribute excluded).
     * @return An array double[] with the features.
     */
    public double[] getFeatures() {
    	double[] filteredFeatures = new double[features.length-1];
    	for (int i = 0; iDataObject.
     * @return An int with the id of the DataObject.
     */
    public int getId() {
        return id;
    }
    public void setId(int id){
    	this.id=id;
    }
    
    /**
     * Return the label for the DataObject.
     * @return An int which codes the label.
     */
    public int getClassLabel() {
        return classLabel;
    }
    
    /**
     * Return the Instance of the DataObject.
     * @return An Instance.
     */
    public Instance getInstance() {
        return inst;
    }
    /**
     * Standard constructor for DataObject.
     * @param idCounter The id for the DataObject.
     * @param features The feature as a double[]
     * @param classLabel The label id for the DataObject.
     */
    public DataObject(int idCounter, Instance inst){
        this.id = idCounter;
        this.inst = inst;
        this.features = inst.toDoubleArray();
        this.classLabel = (int)inst.classValue();
        this.isOutiler = false;
    }
    
    /**
     * Returns the number of features (label attribute excluded).
     * @return The number of features in the point.
     */
    public int getNrOfDimensions(){
        return this.features.length-1;
    }
    
    /**
     * Returns a String representation of the point. The features are written comma
     * separated between parenthesis and the label id is written after the closing parenthesis
     * surrounded by squared brackets.
     * @return A String representation of the point.
     */
    @Override
    public String toString(){
        
        String res = "(";
        for (int i = 0; i < features.length; i++) {
            double d = features[i];
            res += d;
            if (i != features.length - 1)
                res += ",";
        }
        res += ")";
        
        res += "[" + this.classLabel + "]";
        
        return res;
        
    }

    
    public void setOutiler(boolean val) {
		isOutiler = val;
	}
    
    public boolean isOutiler() {
		return isOutiler;
	}
    
}