Merge pull request #101 from sanity/TreeBuilderR

Tree builder r
sanity · Mar 8, 2015 · cf5bb08 · cf5bb08
2 parents da04812 + 4539118
commit cf5bb08
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Showing 26 changed files with 483 additions and 188 deletions.
diff --git a/pom.xml b/pom.xml
@@ -31,7 +31,9 @@
     4)  *ANY* change to the master branch (ie. when a feature branch is merged) must
         be accompanied by a bump in version number, regardless of how minor the change.
     -->
-    <version>0.6.1</version>
+
+    <version>0.7.0</version>
+
 
     <repositories>
         <repository>

diff --git a/src/main/java/quickml/supervised/classifier/StaticBuilders.java b/src/main/java/quickml/supervised/classifier/StaticBuilders.java
@@ -13,6 +13,7 @@
 import quickml.supervised.classifier.decisionTree.TreeBuilder;
 import quickml.supervised.classifier.decisionTree.scorers.GiniImpurityScorer;
 import quickml.supervised.classifier.decisionTree.scorers.InformationGainScorer;
+import quickml.supervised.classifier.decisionTree.tree.attributeIgnoringStrategies.IgnoreAttributesWithConstantProbability;
 import quickml.supervised.classifier.downsampling.DownsamplingClassifier;
 import quickml.supervised.classifier.downsampling.DownsamplingClassifierBuilder;
 import quickml.supervised.classifier.randomForest.RandomForest;
@@ -64,7 +65,7 @@ public static Pair<Map<String, Object>, DownsamplingClassifier> getOptimizedDown
                         .iterations(3).build();
         Map<String, Object> bestParams =  optimizer.determineOptimalConfig();
 
-        RandomForestBuilder<ClassifierInstance> randomForestBuilder = new RandomForestBuilder<>(new TreeBuilder<>().ignoreAttributeAtNodeProbability(0.7)).numTrees(24);
+        RandomForestBuilder<ClassifierInstance> randomForestBuilder = new RandomForestBuilder<>(new TreeBuilder<>().attributeIgnoringStrategy(new IgnoreAttributesWithConstantProbability(0.7))).numTrees(24);
         DownsamplingClassifierBuilder<ClassifierInstance> downsamplingClassifierBuilder = new DownsamplingClassifierBuilder<>(randomForestBuilder,0.1);
         downsamplingClassifierBuilder.updateBuilderConfig(bestParams);
 
@@ -91,7 +92,7 @@ private static int getTimeSliceHours(List<ClassifierInstance> trainingData, int
     private static  Map<String, FieldValueRecommender> createConfig() {
         Map<String, FieldValueRecommender> config = Maps.newHashMap();
         config.put(MAX_DEPTH, new FixedOrderRecommender(4, 8, 16));//Integer.MAX_VALUE, 2, 3, 5, 6, 9));
-        config.put(MIN_CAT_ATTR_OCC, new FixedOrderRecommender(7, 14));
+        config.put(MIN_OCCURRENCES_OF_ATTRIBUTE_VALUE, new FixedOrderRecommender(7, 14));
         config.put(MIN_LEAF_INSTANCES, new FixedOrderRecommender(0, 15));
         config.put(DownsamplingClassifierBuilder.MINORITY_INSTANCE_PROPORTION, new FixedOrderRecommender(.1, .2));
         config.put(DEGREE_OF_GAIN_RATIO_PENALTY, new FixedOrderRecommender(1.0, 0.75));

diff --git a/src/main/java/quickml/supervised/classifier/decisionTree/Tree.java b/src/main/java/quickml/supervised/classifier/decisionTree/Tree.java
@@ -21,11 +21,11 @@
  */
 public class Tree extends AbstractClassifier {
     static final long serialVersionUID = 56394564395635672L;
-    public final Node node;
+    public final Node root;
     private Set<Serializable> classifications = new HashSet<>();
 
-    protected Tree(Node tree, Set<Serializable> classifications) {
-        this.node = tree;
+    protected Tree(Node root, Set<Serializable> classifications) {
+        this.root = root;
         this.classifications = classifications;
     }
 
@@ -35,19 +35,19 @@ public Set<Serializable> getClassifications() {
 
     @Override
     public double getProbability(AttributesMap attributes, Serializable classification) {
-        Leaf leaf = node.getLeaf(attributes);
+        Leaf leaf = root.getLeaf(attributes);
         return leaf.getProbability(classification);
     }
 
     @Override
     public double getProbabilityWithoutAttributes(AttributesMap attributes, Serializable classification, Set<String> attributesToIgnore) {
-        return node.getProbabilityWithoutAttributes(attributes, classification, attributesToIgnore);
+        return root.getProbabilityWithoutAttributes(attributes, classification, attributesToIgnore);
     }
 
 
     @Override
     public PredictionMap predict(AttributesMap attributes) {
-        Leaf leaf = node.getLeaf(attributes);
+        Leaf leaf = root.getLeaf(attributes);
         Map<Serializable, Double> probsByClassification = Maps.newHashMap();
         for (Serializable classification : leaf.getClassifications()) {
             probsByClassification.put(classification, leaf.getProbability(classification));
@@ -66,7 +66,7 @@ public PredictionMap predictWithoutAttributes(AttributesMap attributes, Set<Stri
 
     @Override
     public Serializable getClassificationByMaxProb(AttributesMap attributes) {
-        Leaf leaf = node.getLeaf(attributes);
+        Leaf leaf = root.getLeaf(attributes);
         return leaf.getBestClassification();
     }
 
@@ -77,20 +77,20 @@ public boolean equals(final Object o) {
 
         final Tree tree = (Tree) o;
 
-        if (!node.equals(tree.node)) return false;
+        if (!root.equals(tree.root)) return false;
 
         return true;
     }
 
     @Override
     public int hashCode() {
-        return node.hashCode();
+        return root.hashCode();
     }
 
     @Override
     public String toString() {
         StringBuilder dump = new StringBuilder();
-        node.dump(dump);
+        root.dump(dump);
         return dump.toString();
     }
 }