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update classifier

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This commit is contained in:
DOHA 2015-04-21 08:30:11 +02:00
parent cd4927cdb9
commit 42369da868
1 changed files with 13 additions and 10 deletions
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23
spring-security-oauth/src/main/java/org/baeldung/reddit/classifier/RedditClassifier.java
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@ -25,7 +25,7 @@ public class RedditClassifier {
public static int GOOD = 0; public static int GOOD = 0;
public static int BAD = 1; public static int BAD = 1;
public static int MIN_SCORE = 7; public static int MIN_SCORE = 10;
public static int NUM_OF_FEATURES = 1000; public static int NUM_OF_FEATURES = 1000;
private final AdaptiveLogisticRegression classifier; private final AdaptiveLogisticRegression classifier;
@ -42,9 +42,9 @@ public class RedditClassifier {
public RedditClassifier() { public RedditClassifier() {
classifier = new AdaptiveLogisticRegression(2, NUM_OF_FEATURES, new L2()); classifier = new AdaptiveLogisticRegression(2, NUM_OF_FEATURES, new L2());
classifier.setPoolSize(50); classifier.setPoolSize(150);
titleEncoder = new AdaptiveWordValueEncoder("title"); titleEncoder = new AdaptiveWordValueEncoder("title");
titleEncoder.setProbes(1); titleEncoder.setProbes(2);
domainEncoder = new StaticWordValueEncoder("domain"); domainEncoder = new StaticWordValueEncoder("domain");
domainEncoder.setProbes(1); domainEncoder.setProbes(1);
} }
@ -65,13 +65,15 @@ public class RedditClassifier {
} }
public Vector convertPost(String title, String domain, int hour) { public Vector convertPost(String title, String domain, int hour) {
final Vector features = new RandomAccessSparseVector(4); final Vector vector = new RandomAccessSparseVector(NUM_OF_FEATURES);
final int noOfWords = Splitter.onPattern("\\W").omitEmptyStrings().splitToList(title).size(); final List<String> words = Splitter.onPattern("\\W").omitEmptyStrings().splitToList(title);
titleEncoder.addToVector(title, features); vector.set(0, hour);
domainEncoder.addToVector(domain, features); vector.set(1, words.size());
features.set(2, hour); domainEncoder.addToVector(domain, vector);
features.set(3, noOfWords); for (final String word : words) {
return features; titleEncoder.addToVector(word, vector);
}
return vector;
} }
public int classify(Vector features) { public int classify(Vector features) {
@ -106,6 +108,7 @@ public class RedditClassifier {
System.out.println("Eval count ========= Good = " + evalCount[0] + " ___ Bad = " + evalCount[1]); System.out.println("Eval count ========= Good = " + evalCount[0] + " ___ Bad = " + evalCount[1]);
System.out.println("Test result ======== Correct prediction = " + correct + " ----- Wrong prediction = " + wrong); System.out.println("Test result ======== Correct prediction = " + correct + " ----- Wrong prediction = " + wrong);
System.out.println("Test result ======== Correct Good = " + correctCount[0] + " ----- Correct Bad = " + correctCount[1]); System.out.println("Test result ======== Correct Good = " + correctCount[0] + " ----- Correct Bad = " + correctCount[1]);
System.out.println("Test result ======== Good accuracy = " + (correctCount[0] / (evalCount[0] + 0.0)) + " ----- Bad accuracy = " + (correctCount[1] / (evalCount[1] + 0.0)));
this.accuracy = correct / (wrong + correct + 0.0); this.accuracy = correct / (wrong + correct + 0.0);
} }