Package org.apache.mahout.cf.taste.example.kddcup

Examples of org.apache.mahout.cf.taste.example.kddcup.DataFileIterable

64
65
66
67
68
69
70
71
72
73
74
    long end = System.currentTimeMillis();
    log.info("Loaded model in {}s", (end - start) / 1000);
    start = end;

    Collection<Track2Callable> callables = Lists.newArrayList();
    for (Pair<PreferenceArray,long[]> tests : new DataFileIterable(KDDCupDataModel.getTestFile(dataFileDirectory))) {
      PreferenceArray userTest = tests.getFirst();
      callables.add(new Track2Callable(recommender, userTest));
    }

    int cores = Runtime.getRuntime().availableProcessors();
View Full Code Here
64
65
66
67
68
69
70
71
72
73
74
    long end = System.currentTimeMillis();
    log.info("Loaded model in {}s", (end - start) / 1000);
    start = end;

    Collection<Track1Callable> callables = Lists.newArrayList();
    for (Pair<PreferenceArray,long[]> tests : new DataFileIterable(KDDCupDataModel.getTestFile(dataFileDirectory))) {
      PreferenceArray userTest = tests.getFirst();
      callables.add(new Track1Callable(recommender, userTest));
    }

    int cores = Runtime.getRuntime().availableProcessors();
View Full Code Here
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
    log.info("Estimating validation preferences...");
    int prefsProcessed = 0;
    RunningAverage average = new FullRunningAverage();
    for (Pair<PreferenceArray,long[]> validationPair
        : new DataFileIterable(KDDCupDataModel.getValidationFile(dataFileDirectory))) {
      for (Preference validationPref : validationPair.getFirst()) {
        double estimate = estimatePreference(factorization, validationPref.getUserID(), validationPref.getItemID(),
            factorizablePreferences.getMinPreference(), factorizablePreferences.getMaxPreference());
        double error = validationPref.getValue() - estimate;
        average.addDatum(error * error);
        prefsProcessed++;
        if (prefsProcessed % 100000 == 0) {
          log.info("Computed {} estimations", prefsProcessed);
        }
      }
    }
    log.info("Computed {} estimations, done.", prefsProcessed);

    double rmse = Math.sqrt(average.getAverage());
    log.info("RMSE {}", rmse);

    log.info("Estimating test preferences...");
    OutputStream out = null;
    try {
      out = new BufferedOutputStream(new FileOutputStream(resultFile));

      for (Pair<PreferenceArray,long[]> testPair
          : new DataFileIterable(KDDCupDataModel.getTestFile(dataFileDirectory))) {
        for (Preference testPref : testPair.getFirst()) {
          double estimate = estimatePreference(factorization, testPref.getUserID(), testPref.getItemID(),
              factorizablePreferences.getMinPreference(), factorizablePreferences.getMaxPreference());
          byte result = EstimateConverter.convert(estimate, testPref.getUserID(), testPref.getItemID());
          out.write(result);
View Full Code Here
47
48
49
50
51
52
53
54
55
56
57
  }

  @Override
  public Iterable<Preference> getPreferences() {
    Iterable<Iterable<Preference>> prefIterators =
        Iterables.transform(new DataFileIterable(dataFile),
          new Function<Pair<PreferenceArray,long[]>,Iterable<Preference>>() {
            @Override
            public Iterable<Preference> apply(Pair<PreferenceArray,long[]> from) {
              return from.getFirst();
            }
View Full Code Here
70
71
72
73
74
75
76
77
78
79
80
    Recommender recommender = recommenderBuilder.buildRecommender(dataModel);

    Collection<Callable<Void>> estimateCallables = Lists.newArrayList();
    AtomicInteger noEstimateCounter = new AtomicInteger();
    for (Pair<PreferenceArray,long[]> userData
        : new DataFileIterable(KDDCupDataModel.getValidationFile(dataFileDirectory))) {
      PreferenceArray validationPrefs = userData.getFirst();
      long userID = validationPrefs.get(0).getUserID();
      estimateCallables.add(
          new PreferenceEstimateCallable(recommender, userID, validationPrefs, noEstimateCounter));
    }
View Full Code Here
63
64
65
66
67
68
69
70
71
72
73
    long end = System.currentTimeMillis();
    log.info("Loaded model in {}s", (end - start) / 1000);
    start = end;

    Collection<Track1Callable> callables = new ArrayList<Track1Callable>();
    for (Pair<PreferenceArray,long[]> tests : new DataFileIterable(KDDCupDataModel.getTestFile(dataFileDirectory))) {
      PreferenceArray userTest = tests.getFirst();
      callables.add(new Track1Callable(recommender, userTest));
    }

    int cores = Runtime.getRuntime().availableProcessors();
View Full Code Here
68
69
70
71
72
73
74
75
76
77
78
    Recommender recommender = recommenderBuilder.buildRecommender(dataModel);

    Collection<Callable<Void>> estimateCallables = new ArrayList<Callable<Void>>();
    AtomicInteger noEstimateCounter = new AtomicInteger();
    for (Pair<PreferenceArray,long[]> userData :
         new DataFileIterable(KDDCupDataModel.getValidationFile(dataFileDirectory))) {
      PreferenceArray validationPrefs = userData.getFirst();
      long userID = validationPrefs.get(0).getUserID();
      estimateCallables.add(
          new PreferenceEstimateCallable(recommender, userID, validationPrefs, noEstimateCounter));
    }
View Full Code Here
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
    Factorization factorization = sgdFactorizer.factorize();

    log.info("Estimating validation preferences...");
    int prefsProcessed = 0;
    RunningAverage average = new FullRunningAverage();
    DataFileIterable validations = new DataFileIterable(KDDCupDataModel.getValidationFile(dataFileDirectory));
    for (Pair<PreferenceArray,long[]> validationPair : validations) {
      for (Preference validationPref : validationPair.getFirst()) {
        double estimate = estimatePreference(factorization, validationPref.getUserID(), validationPref.getItemID(),
            factorizablePreferences.getMinPreference(), factorizablePreferences.getMaxPreference());
        double error = validationPref.getValue() - estimate;
        average.addDatum(error * error);
        prefsProcessed++;
        if (prefsProcessed % 100000 == 0) {
          log.info("Computed {} estimations", prefsProcessed);
        }
      }
    }
    log.info("Computed {} estimations, done.", prefsProcessed);

    double rmse = Math.sqrt(average.getAverage());
    log.info("RMSE {}", rmse);

    log.info("Estimating test preferences...");
    OutputStream out = null;
    try {
      out = new BufferedOutputStream(new FileOutputStream(resultFile));

      DataFileIterable tests = new DataFileIterable(KDDCupDataModel.getTestFile(dataFileDirectory));
      for (Pair<PreferenceArray,long[]> testPair : tests) {
        for (Preference testPref : testPair.getFirst()) {
          double estimate = estimatePreference(factorization, testPref.getUserID(), testPref.getItemID(),
              factorizablePreferences.getMinPreference(), factorizablePreferences.getMaxPreference());
          byte result = EstimateConverter.convert(estimate, testPref.getUserID(), testPref.getItemID());
View Full Code Here
47
48
49
50
51
52
53
54
55
56
57
  }

  @Override
  public Iterable<Preference> getPreferences() {
    Iterable<Iterable<Preference>> prefIterators =
        Iterables.transform(new DataFileIterable(dataFile),
                            new Function<Pair<PreferenceArray,long[]>,Iterable<Preference>>() {
                              @Override
                              public Iterable<Preference> apply(Pair<PreferenceArray,long[]> from) {
                                return from.getFirst();
                              }
View Full Code Here
63
64
65
66
67
68
69
70
71
72
73
    long end = System.currentTimeMillis();
    log.info("Loaded model in {}s", (end - start) / 1000);
    start = end;

    Collection<Track2Callable> callables = new ArrayList<Track2Callable>();
    for (Pair<PreferenceArray,long[]> tests : new DataFileIterable(KDDCupDataModel.getTestFile(dataFileDirectory))) {
      PreferenceArray userTest = tests.getFirst();
      callables.add(new Track2Callable(recommender, userTest));
    }

    int cores = Runtime.getRuntime().availableProcessors();
View Full Code Here
TOP

Related Classes of org.apache.mahout.cf.taste.example.kddcup.DataFileIterable

  • org.apache.mahout.cf.taste.example.kddcup.track1.svd.KDDCupFactorizablePreferences
  • org.apache.mahout.cf.taste.example.kddcup.track1.svd.Track1SVDRunner
  • org.apache.mahout.cf.taste.example.kddcup.track1.Track1RecommenderEvaluator
  • org.apache.mahout.cf.taste.example.kddcup.track1.Track1Runner
  • org.apache.mahout.cf.taste.example.kddcup.track2.Track2Runner
    • Copyright © 2018 www.massapicom. All rights reserved.
    All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.