com.guidefreitas.locator.services.PredictionService.java Source code

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Here is the source code for com.guidefreitas.locator.services.PredictionService.java

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package com.guidefreitas.locator.services;

import com.guidefreitas.locator.model.AccessPoint;
import com.guidefreitas.locator.model.LocationData;
import com.guidefreitas.locator.model.PredictionRequest;
import com.guidefreitas.locator.model.Room;
import java.io.ByteArrayInputStream;
import java.io.InputStream;
import java.io.StringReader;
import java.nio.charset.StandardCharsets;
import java.util.HashMap;
import java.util.Hashtable;
import java.util.List;
import java.util.Map;
import java.util.Random;
import java.util.logging.Level;
import java.util.logging.Logger;
import weka.classifiers.Evaluation;
import weka.classifiers.functions.LibSVM;
import weka.core.Instances;
import weka.core.SelectedTag;
import weka.core.converters.ConverterUtils.DataSource;

/**
 *
 * @author guilherme
 */
public class PredictionService {
    private static PredictionService instance;
    private LibSVM classifier;

    public static PredictionService getInstance() {
        if (instance == null) {
            instance = new PredictionService();
        }

        return instance;
    }

    private PredictionService() {

    }

    public String generateTestData(PredictionRequest req) {
        try {
            StringBuilder sb = new StringBuilder();
            List<AccessPoint> aps = LocationService.getInstance().getAccessPoints();
            sb.append("@RELATION wifi\n");
            sb.append("\n");
            for (AccessPoint ap : aps) {
                sb.append("@ATTRIBUTE ap" + ap.getId() + " REAL\n");
            }
            List<Room> rooms = RoomService.getInstance().getAll();
            sb.append("@ATTRIBUTE class {");
            for (int i = 0; i < rooms.size(); i++) {
                Room room = rooms.get(i);
                sb.append(room.getId());
                if (i != rooms.size() - 1)
                    sb.append(",");
            }
            sb.append(",none");
            sb.append("}\n");
            sb.append("\n");
            sb.append("@DATA\n");

            for (int c = 0; c < aps.size(); c++) {
                AccessPoint ap = aps.get(c);
                Map<String, Float> coletaData = req.getAccessPointData();
                if (coletaData.containsKey(ap.getBssid())) {
                    sb.append(coletaData.get(ap.getBssid()));
                } else {
                    sb.append("0");
                }
                if (c != aps.size() - 1) {
                    sb.append(",");
                } else {
                    sb.append(",none");
                    sb.append("\n");
                }
            }

            return sb.toString();

        } catch (Exception ex) {
            Logger.getLogger(PredictionService.class.getName()).log(Level.SEVERE, null, ex);
        }

        return null;
    }

    public String generateTrainData() {
        try {
            StringBuilder sb = new StringBuilder();
            List<AccessPoint> aps = LocationService.getInstance().getAccessPoints();
            sb.append("@RELATION wifi\n");
            sb.append("\n");
            for (AccessPoint ap : aps) {
                sb.append("@ATTRIBUTE ap" + ap.getId() + " REAL\n");
            }
            List<Room> rooms = RoomService.getInstance().getAll();
            sb.append("@ATTRIBUTE class {");
            for (int i = 0; i < rooms.size(); i++) {
                Room room = rooms.get(i);
                sb.append(room.getId());
                if (i != rooms.size() - 1)
                    sb.append(",");
            }
            sb.append(",none");
            sb.append("}\n");
            sb.append("\n");
            sb.append("@DATA\n");
            List<LocationData> locData = LocationService.getInstance().getAllLocationData();

            HashMap<String, HashMap<Long, Float>> data = new HashMap<String, HashMap<Long, Float>>();

            for (LocationData loc : locData) {
                String uuid = loc.getUuid();
                for (AccessPoint ap : aps) {
                    if (loc.getAccessPoint().getId().equals(ap.getId())) {
                        if (!data.containsKey(uuid)) {
                            data.put(uuid, new HashMap<Long, Float>());
                        }
                        data.get(uuid).put(ap.getId(), loc.getSignalIntesity());
                    }

                }
            }

            for (String key : data.keySet()) {
                for (int c = 0; c < aps.size(); c++) {
                    AccessPoint ap = aps.get(c);
                    Map<Long, Float> coletaData = data.get(key);
                    if (coletaData.containsKey(ap.getId())) {
                        sb.append(coletaData.get(ap.getId()));
                    } else {
                        sb.append("0");
                    }
                    if (c != aps.size() - 1) {
                        sb.append(",");
                    } else {
                        String category = LocationService.getInstance().getLocationDataByUUID(key).getRoom().getId()
                                .toString();
                        sb.append("," + category);
                        sb.append("\n");
                    }
                }
            }

            return sb.toString();

        } catch (Exception ex) {
            Logger.getLogger(PredictionService.class.getName()).log(Level.SEVERE, null, ex);
        }

        return null;
    }

    public Evaluation train() {
        try {
            String arffData = this.generateTrainData();
            InputStream stream = new ByteArrayInputStream(arffData.getBytes(StandardCharsets.UTF_8));
            DataSource source = new DataSource(stream);
            Instances data = source.getDataSet();
            data.setClassIndex(data.numAttributes() - 1);
            this.classifier = new LibSVM();
            this.classifier.setKernelType(new SelectedTag(LibSVM.KERNELTYPE_POLYNOMIAL, LibSVM.TAGS_KERNELTYPE));
            this.classifier.setSVMType(new SelectedTag(LibSVM.SVMTYPE_C_SVC, LibSVM.TAGS_SVMTYPE));

            Evaluation eval = new Evaluation(data);
            eval.crossValidateModel(this.classifier, data, 10, new Random(1));

            this.classifier.buildClassifier(data);
            return eval;
        } catch (Exception ex) {
            Logger.getLogger(PredictionService.class.getName()).log(Level.SEVERE, null, ex);
        }

        return null;
    }

    public Room predict(PredictionRequest request) {
        try {

            String arffData = this.generateTestData(request);
            StringReader reader = new StringReader(arffData);
            Instances unlabeled = new Instances(reader);
            System.out.println("Test data size: " + unlabeled.size());
            unlabeled.setClassIndex(unlabeled.numAttributes() - 1);
            Instances labeled = new Instances(unlabeled);
            Double clsLabel = this.classifier.classifyInstance(unlabeled.get(0));
            labeled.instance(0).setClassValue(clsLabel);
            String roomIdString = unlabeled.classAttribute().value(clsLabel.intValue());

            Long roomId = Long.parseLong(roomIdString);
            Room predictedRoom = RoomService.getInstance().getById(roomId);
            System.out.println(clsLabel + " -> " + roomIdString + " -> " + predictedRoom.getName());
            return predictedRoom;

        } catch (Exception ex) {
            Logger.getLogger(PredictionService.class.getName()).log(Level.SEVERE, null, ex);
        }
        return null;
    }
}