Merge pull request eugenp#200 from Doha2012/master

minor changes to reddit classifier

Author: Eugen

spring-security-oauth/src/main/java/org/baeldung/reddit/classifier/RedditClassifier.java

@@ -24,7 +24,6 @@
 public class RedditClassifier {
     public static int GOOD = 0;
     public static int BAD = 1;
-    public static int MIN_SCORE = 7;
 
     private final int[] trainCount = { 0, 0 };
     private final int[] evalCount = { 0, 0 };
@@ -34,15 +33,16 @@ public class RedditClassifier {
     private final FeatureVectorEncoder titleEncoder;
     private final FeatureVectorEncoder domainEncoder;
     private final int noOfFeatures;
-
+    private final int minScore;
     private CrossFoldLearner learner;
     private double accuracy;
 
     public RedditClassifier() {
-        this(150, 1000);
+        this(150, 1000, 7);
     }
 
-    public RedditClassifier(final int poolSize, final int noOfFeatures) {
+    public RedditClassifier(final int poolSize, final int noOfFeatures, int minScore) {
+        this.minScore = minScore;
         this.noOfFeatures = noOfFeatures;
         classifier = new AdaptiveLogisticRegression(2, noOfFeatures, new L2());
         classifier.setPoolSize(poolSize);
@@ -154,20 +154,15 @@ private NamedVector extractVector(final String line) {
         internalVector.set(1, Integer.parseInt(numberOfWordInTitle)); // number of words in the title
 
         domainEncoder.addToVector(theRootDomain, internalVector);
-        final String[] words = title.split(" ");
-        // titleEncoder.setProbes(words.length);
-
-        // TODO: use a Java 8 stream with filter and remove the 1 and 2 character words; example: "a", "of", "to"
-        for (final String word : words) {
-            titleEncoder.addToVector(word, internalVector);
-        }
+        final List<String> words = Splitter.on(' ').splitToList(title);
+        words.stream().filter(word -> word.length() > 2).forEach(word -> titleEncoder.addToVector(word, internalVector));
 
         final String category = extractCategory(Integer.parseInt(numberOfVotes));
         return new NamedVector(internalVector, category);
     }
 
     private String extractCategory(final int score) {
-        return (score < MIN_SCORE) ? "BAD" : "GOOD";
+        return (score < minScore) ? "BAD" : "GOOD";
     }
 
 }

spring-security-oauth/src/main/java/org/baeldung/reddit/classifier/RedditDataCollector.java

@@ -27,11 +27,7 @@ public class RedditDataCollector {
     private final String subreddit;
 
     public RedditDataCollector() {
-        restTemplate = new RestTemplate();
-        final List<ClientHttpRequestInterceptor> list = new ArrayList<ClientHttpRequestInterceptor>();
-        list.add(new UserAgentInterceptor());
-        restTemplate.setInterceptors(list);
-        subreddit = "java";
+        this("java");
     }
 
     public RedditDataCollector(String subreddit) {

spring-security-oauth/src/test/java/org/baeldung/classifier/RedditClassifierTest.java

@@ -23,7 +23,7 @@ public void whenUsingDefaultClassifier_thenAccurate() throws IOException {
 
     @Test
     public void givenSmallerPoolSizeAndFeatures_whenUsingCustomClassifier_thenAccurate() throws IOException {
-        final RedditClassifier classifier = new RedditClassifier(100, 500);
+        final RedditClassifier classifier = new RedditClassifier(100, 500, 7);
         classifier.trainClassifier(RedditDataCollector.DATA_FILE);
         final double result = classifier.getAccuracy();
         System.out.println("==== Custom Classifier (small) Accuracy = " + result);
@@ -33,7 +33,7 @@ public void givenSmallerPoolSizeAndFeatures_whenUsingCustomClassifier_thenAccura
 
     @Test
     public void givenLargerPoolSizeAndFeatures_whenUsingCustomClassifier_thenAccurate() throws IOException {
-        final RedditClassifier classifier = new RedditClassifier(250, 2500);
+        final RedditClassifier classifier = new RedditClassifier(250, 2500, 7);
         classifier.trainClassifier(RedditDataCollector.DATA_FILE);
         final double result = classifier.getAccuracy();
         System.out.println("==== Custom Classifier (large) Accuracy = " + result);