Refactoring.

Author: felipexw

src/main/java/com/github/felipexw/classifiers/bayes/MultinomialNaiveBayesClassifier.java

@@ -1,8 +1,6 @@
 package com.github.felipexw.classifiers.bayes;
 
-import com.github.felipexw.core.Instance;
-import com.github.felipexw.core.LabeledInstance;
-import com.github.felipexw.core.Prediction;
+import com.github.felipexw.core.*;
 
 import java.util.ArrayList;
 import java.util.HashMap;
@@ -56,10 +54,10 @@ public void calculateProbs(List<LabeledInstance> instanceList) {
         if (instanceList == null || instanceList.isEmpty())
             throw new IllegalArgumentException("Args can't be null");
 
-        for (LabeledInstance<String, Double> instance : instanceList) {
-            String key = instance.getLabel();
+        for (LabeledInstance<Label, Model> instance : instanceList) {
+            String key = instance.getLabel().toString();
             if (!labels.containsKey(key)) {
-                labels.put(instance.getLabel(), 1);
+                labels.put(instance.getLabel().toString(), 1);
             }
             else{
                 labels.put(key, labels.get(key)+1);
@@ -88,9 +86,9 @@ public void calculatePosterioriProbability(LabeledInstance instance) {
          */
     }
 
-    private void countFromLabels(List<LabeledInstance<String, Double>> instances, LabeledInstance<String, Double> instance) {
-        for (LabeledInstance<String, Double> featuresInstance : instances) {
-            if (featuresInstance.getLabel().equalsIgnoreCase(instance.getLabel())) {
+    private void countFromLabels(List<LabeledInstance<Label, Model>> instances, LabeledInstance<Label, Model> instance) {
+        for (LabeledInstance<Label, Model> featuresInstance : instances) {
+            if (featuresInstance.getLabel().toString().equalsIgnoreCase(instance.getLabel().toString())) {
                 featuresInstance.setCount(featuresInstance.getCount() + 1);
             } else {
                 instance.setCount(1);

src/main/java/com/github/felipexw/classifiers/neighbors/KNNClassifier.java

@@ -2,6 +2,7 @@
 
 import com.github.felipexw.classifiers.Classifier;
 import com.github.felipexw.core.CrossValidation;
+import com.github.felipexw.core.extraction.FeatureExtractor;
 import com.github.felipexw.evaluations.metrics.SimilarityCalculator;
 import com.github.felipexw.core.LabeledInstance;
 import com.github.felipexw.core.Prediction;
@@ -18,6 +19,7 @@ public abstract class KNNClassifier implements Classifier, CrossValidation {
     protected Map<Neighbor, List<Neighbor>> features;
     protected List<LabeledInstance> instances;
     protected SimilarityCalculator similarityCalculator;
+    protected FeatureExtractor featureExtractor;
 
     public abstract Prediction vote(List<Neighbor> neighbors);
 

src/main/java/com/github/felipexw/classifiers/neighbors/Neighbor.java

@@ -1,15 +1,18 @@
 package com.github.felipexw.classifiers.neighbors;
 
 import com.github.felipexw.core.LabeledInstance;
+import com.github.felipexw.core.Model;
+import com.github.felipexw.core.extraction.FeatureExtractor;
 
 /**
  * Created by felipe.appio on 24/08/2016.
  */
-public class Neighbor {
-    private final LabeledInstance instance;
-    private final double distance;
+public class Neighbor extends  Model {
+    private LabeledInstance instance;
+    private double distance;
 
-    public Neighbor(LabeledInstance instance, double distance) {
+    public Neighbor(LabeledInstance instance, double distance, FeatureExtractor featureExtractor) {
+        super(featureExtractor);
         this.instance = instance;
         this.distance = distance;
     }

src/main/java/com/github/felipexw/classifiers/neighbors/SimpleKNNClassifier.java

@@ -1,23 +1,22 @@
 package com.github.felipexw.classifiers.neighbors;
 
+import com.github.felipexw.core.*;
+import com.github.felipexw.core.extraction.DoubleFeatureExtractor;
+import com.github.felipexw.core.extraction.FeatureExtractor;
 import com.github.felipexw.evaluations.EvaluatorMetric;
 import com.github.felipexw.evaluations.metrics.SimilarityCalculator;
-import com.github.felipexw.core.Instance;
-import com.github.felipexw.core.LabeledInstance;
-import com.github.felipexw.core.Prediction;
 import com.google.common.collect.ImmutableMap;
 import com.google.common.collect.Lists;
 
 import java.util.*;
-import java.util.List;
 
 /**
  * Created by felipe.appio on 23/08/2016.
  */
 public class SimpleKNNClassifier extends KNNClassifier {
 
 
-    public SimpleKNNClassifier(SimilarityCalculator similarityCalculator) {
+    public SimpleKNNClassifier(SimilarityCalculator similarityCalculator, FeatureExtractor featureExtractor) {
         this.similarityCalculator = similarityCalculator;
         k = 5;
     }
@@ -53,7 +52,7 @@ protected List<LabeledInstance> getInstancesthatMaximizeAccuracy() {
                 for (List<LabeledInstance> labeled : partitionedInstances) {
                     for (LabeledInstance instance : labeled) {
                         if (i != testIndex) {
-                            Neighbor neighbor = new Neighbor(instance, -1d);
+                            Neighbor neighbor = new Neighbor(instance, -1d, featureExtractor);
                             List<Neighbor> neighbors = getNeighborsWithDistanceFromARootNeighboor(neighbor, k);
                             features.put(neighbor, neighbors);
                         } else
@@ -129,24 +128,29 @@ protected void setUpForTraining(List<LabeledInstance> instances) {
     protected void calculateFeatureSimilarities() {
         for (int i = 0; i < instances.size(); i++) {
             LabeledInstance instance = instances.get(i);
-            Neighbor neighbor = new Neighbor(instance, -1d);
+            Neighbor neighbor = new Neighbor(instance, -1d, featureExtractor);
 
             List<Neighbor> neighbors = getNeighborsWithDistanceFromARootNeighboor(neighbor, this.k);
             features.put(neighbor, neighbors);
         }
     }
 
     protected List<Neighbor> getNeighborsWithDistanceFromARootNeighboor(Neighbor neighbor, int threshold) {
-        throw new UnsupportedOperationException("Continue the implementation");
 
+
+//        LabeledInstance<Double, String> t = new LabeledInstance<>("2");
+
+
+        Neighbor nei = new Neighbor(null, 0d, featureExtractor);
         List<Neighbor> neighbors = new ArrayList<>();
+
         LabeledInstance instance = neighbor.getInstance();
 
         for (int j = -1; j < instances.size() - 1; j++) {
             LabeledInstance neighborInstance = instances.get(j + 1);
 //            double similarity = similarityCalculator.calculate(instance.getFeatures(), neighborInstance.getFeatures());
             double similarity = 0d;
-            Neighbor neighborRoot = new Neighbor(neighborInstance, similarity);
+            Neighbor neighborRoot = new Neighbor(neighborInstance, similarity, new DoubleFeatureExtractor());
             neighbors.add(neighborRoot);
             if (neighbors.size() == threshold)
                 return neighbors;
@@ -163,7 +167,7 @@ public List<Neighbor> similarNeighbors(LabeledInstance trainingInstance, int k)
         if (features.containsKey(trainingInstance))
             features.get(trainingInstance);
 
-        Neighbor neighbor1 = new Neighbor(trainingInstance, -1d);
+        Neighbor neighbor1 = new Neighbor(trainingInstance, -1d, featureExtractor);
         return getNeighborsWithDistanceFromARootNeighboor(neighbor1, k);
     }
 
@@ -209,13 +213,13 @@ public Prediction vote(List<Neighbor> neighbors) {
         Map<String, Integer> votes = new HashMap<>();
 
         for (Neighbor neighbor : neighbors) {
-            LabeledInstance<String, Double> instance = neighbor.getInstance();
+            LabeledInstance<Label, Model> instance = neighbor.getInstance();
             if (!votes.containsKey(instance.getLabel()))
-                votes.put(instance.getLabel(), 1);
+                votes.put(instance.getLabel().toString(), 1);
 
             else {
                 Integer count = votes.get(instance.getLabel());
-                votes.put(instance.getLabel(), count + 1);
+                votes.put(instance.getLabel().toString(), count + 1);
             }
 
         }
@@ -250,8 +254,8 @@ protected int getIndexOfNearestNeighboorVoted(String label, List<Neighbor> neigh
 
         for (int i = 0; i < neighbors.size(); i++) {
             Neighbor neighbor = neighbors.get(i);
-            LabeledInstance<String, Double> instance = neighbor.getInstance();
-            if (instance.getLabel().equalsIgnoreCase(label) && neighbor.getDistance() < distance) {
+            LabeledInstance<Label, Model> instance = neighbor.getInstance();
+            if (instance.getLabel().toString().equalsIgnoreCase(label) && neighbor.getDistance() < distance) {
                 distance = neighbor.getDistance();
                 index = i;
             }

src/main/java/com/github/felipexw/core/Instance.java

@@ -5,7 +5,7 @@
 /**
  * Created by felipe.appio on 23/08/2016.
  */
-public abstract class Instance<F> {
+public class Instance<F> {
     protected  List<F> features;
 
     public List<F> getFeatures() {

src/main/java/com/github/felipexw/core/Label.java

@@ -0,0 +1,16 @@
+package com.github.felipexw.core;
+
+/**
+ * Created by felipe.appio on 31/08/2016.
+ */
+public class Label<T> {
+    private final T label;
+
+    public T getLabel() {
+        return label;
+    }
+
+    public Label(T label) {
+        this.label = label;
+    }
+}

src/main/java/com/github/felipexw/core/LabeledInstance.java

@@ -1,25 +1,32 @@
 package com.github.felipexw.core;
 
+import java.util.Objects;
+
 /**
  * Created by felipe.appio on 23/08/2016.
  */
-public class LabeledInstance<L, F> extends Instance<F> {
-  protected final L label;
-  private int count;
+public class LabeledInstance<L extends Label, F extends Model> extends Instance<String> {
+    protected L label;
+    private int count;
+
+    public LabeledInstance(L label) {
+        this.label = label;
+    }
 
-  public LabeledInstance(L label) {
-    this.label = label;
-  }
+    public L getLabel() {
+        return this.label;
+    }
 
-  public L getLabel() {
-    return this.label;
-  }
+    @Override
+    public String toString() {
+        return label.toString();
+    }
 
-  public void setCount(int count) {
-    this.count = count;
-  }
+    public void setCount(int count) {
+        this.count = count;
+    }
 
-  public int getCount() {
-    return count;
-  }
+    public int getCount() {
+        return count;
+    }
 }

src/main/java/com/github/felipexw/core/Model.java

@@ -0,0 +1,23 @@
+package com.github.felipexw.core;
+
+import com.github.felipexw.core.extraction.FeatureExtractor;
+import com.github.felipexw.core.extraction.FeatureVector;
+
+import java.util.List;
+
+/**
+ * Created by felipe.appio on 31/08/2016.
+ */
+public class Model implements FeatureVector {
+
+    private FeatureExtractor featureExtractor;
+
+    public Model(FeatureExtractor featureExtractor) {
+        this.featureExtractor = featureExtractor;
+    }
+
+    @Override
+    public List getData(List source) {
+        return  featureExtractor.extract(source);
+    }
+}

src/main/java/com/github/felipexw/core/extraction/DoubleFeatureExtractor.java

@@ -0,0 +1,16 @@
+package com.github.felipexw.core.extraction;
+
+import java.util.Arrays;
+import java.util.List;
+import java.util.Objects;
+
+/**
+ * Created by felipe.appio on 31/08/2016.
+ */
+public class DoubleFeatureExtractor implements FeatureExtractor<Double>{
+
+    @Override
+    public List<Double> extract(List<Object> source) {
+        return Arrays.asList(new Double(1d), new Double(2d), new Double(3d), new Double(4d));
+    }
+}

src/main/java/com/github/felipexw/core/extraction/FeatureExtractor.java

@@ -0,0 +1,10 @@
+package com.github.felipexw.core.extraction;
+
+import java.util.List;
+
+/**
+ * Created by felipe.appio on 31/08/2016.
+ */
+public interface FeatureExtractor<T> {
+    List<T> extract(List<Object> source);
+}