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minor cleanup

This commit is contained in:
eugenp 2015-04-22 12:37:17 +03:00
parent 1175f22a99
commit cddb1ed328
1 changed files with 27 additions and 16 deletions
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43
spring-security-oauth/src/main/java/org/baeldung/reddit/classifier/RedditClassifier.java
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@ -50,7 +50,7 @@ public class RedditClassifier {
domainEncoder.setProbes(1);
}
public RedditClassifier(int poolSize, int noOfFeatures) {
public RedditClassifier(final int poolSize, final int noOfFeatures) {
this.noOfFeatures = noOfFeatures;
classifier = new AdaptiveLogisticRegression(2, noOfFeatures, new L2());
classifier.setPoolSize(poolSize);
@ -60,7 +60,7 @@ public class RedditClassifier {
domainEncoder.setProbes(1);
}
public void trainClassifier(String fileName) throws IOException {
public void trainClassifier(final String fileName) throws IOException {
final List<NamedVector> vectors = extractVectors(readDataFile(fileName));
final int size = vectors.size();
final int noOfTraining = (int) (size * 0.8);
@ -77,7 +77,7 @@ public class RedditClassifier {
evaluateClassifier(testData);
}
public Vector convertPost(String title, String domain, int hour) {
public Vector convertPost(final String title, final String domain, final int hour) {
final Vector vector = new RandomAccessSparseVector(noOfFeatures);
final List<String> words = Splitter.onPattern("\\W").omitEmptyStrings().splitToList(title);
vector.set(0, hour);
@ -89,7 +89,7 @@ public class RedditClassifier {
return vector;
}
public int classify(Vector features) {
public int classify(final Vector features) {
if (learner == null) {
learner = classifier.getBest().getPayload().getLearner();
}
@ -102,7 +102,7 @@ public class RedditClassifier {
// ==== Private methods
private void evaluateClassifier(List<NamedVector> vectors) throws IOException {
private void evaluateClassifier(final List<NamedVector> vectors) throws IOException {
int category, result;
int correct = 0;
int wrong = 0;
@ -125,7 +125,7 @@ public class RedditClassifier {
this.accuracy = correct / (wrong + correct + 0.0);
}
private List<String> readDataFile(String fileName) throws IOException {
private List<String> readDataFile(final String fileName) throws IOException {
List<String> lines = Files.readLines(new File(fileName), Charset.forName("utf-8"));
if ((lines == null) || (lines.size() == 0)) {
new RedditDataCollector().collectData();
@ -135,7 +135,7 @@ public class RedditClassifier {
return lines;
}
private List<NamedVector> extractVectors(List<String> lines) {
private List<NamedVector> extractVectors(final List<String> lines) {
final List<NamedVector> vectors = new ArrayList<NamedVector>(lines.size());
for (final String line : lines) {
vectors.add(extractVector(line));
@ -143,25 +143,36 @@ public class RedditClassifier {
return vectors;
}
private NamedVector extractVector(String line) {
private NamedVector extractVector(final String line) {
final String[] items = line.split(",");
final String category = extractCategory(Integer.parseInt(items[0]));
final NamedVector vector = new NamedVector(new RandomAccessSparseVector(noOfFeatures), category);
final Calendar cal = Calendar.getInstance(TimeZone.getTimeZone("GMT"));
cal.setTimeInMillis(Long.parseLong(items[1]) * 1000);
final String numberOfVotes = items[0];
final String time = items[1];
final String numberOfWordInTitle = items[2];
final String title = items[3];
final String theRootDomain = items[4];
final String category = extractCategory(Integer.parseInt(numberOfVotes));
final NamedVector vector = new NamedVector(new RandomAccessSparseVector(noOfFeatures), category);
final Calendar cal = Calendar.getInstance(TimeZone.getTimeZone("GMT"));
cal.setTimeInMillis(Long.parseLong(time) * 1000);
vector.set(0, cal.get(Calendar.HOUR_OF_DAY)); // hour of day
vector.set(1, Integer.parseInt(items[2])); // number of words in the title
domainEncoder.addToVector(items[4], vector);
final String[] words = items[3].split(" ");
vector.set(1, Integer.parseInt(numberOfWordInTitle)); // number of words in the title
domainEncoder.addToVector(theRootDomain, vector);
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, vector);
}
return vector;
}
private String extractCategory(int score) {
private String extractCategory(final int score) {
return (score < MIN_SCORE) ? "BAD" : "GOOD";
}