Package org.apache.mahout.math.Vector

Examples of org.apache.mahout.math.Vector.Element

117
118
119
120
121
122
123
124
125
126
            Vector tmp = userItemMatrix.get(userid);
            Iterator<Element> iter = tmp.iterateNonZero();

            while (iter.hasNext()) {
                Element el = iter.next();
                int itemid = el.index();
            }
        }
    }
View Full Code Here
108
109
110
111
112
113
114
115
116
117
118
            int userid = users.get(i);
            Vector tmp = datamodel.getVectorOfItems(userid);
            Iterator<Element> iter = tmp.iterateNonZero();
            double rate = 0.0;
            while (iter.hasNext()) {
                Element e = iter.next();
                rate += (e.get() - mean - bitems.get(e.index()));
            }
            busers.put(userid, rate / (tmp.getNumNondefaultElements() + lamda3));
        }
    }
View Full Code Here
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
                PreferenceArray UserFactor = pusers.get(userid);
                for (int k = 0; k < parameter_k; k++) {
                    Iterator<Element> itor = tmpitems.iterateNonZero();
                    double sum = 0.0;
                    while (itor.hasNext()) {
                        Element e = itor.next();
                        int itemid = e.index();
                        sum = sum + y.get(itemid).getValue(k);
                    }
                    float temp = (float) (UserFactor.getValue(k) + sum
                            / Math.sqrt(nu));
                    tempUserFactor.setValue(k, temp);

                    sumQE.setValue(k, 0.0f);
                }

                // iterate to deal with items
                Iterator<Element> itor = tmpitems.iterateNonZero();
                while (itor.hasNext()) {

                    Element e = itor.next();
                    int itemid = e.index();

                    // actual rating and estimated rating
                    double rui = datamodel.getPreferenceValue(userid, itemid);
                    double pui = predictPreference(userid, itemid);
                    double eui = rui - pui;

                    rmse += eui * eui;
                    n++;

                    // update bias values
                    double tmp = busers.get(userid) + gamma1
                            * (eui - lamda6 * busers.get(userid));
                    busers.put(userid, tmp);
                    tmp = bitems.get(itemid) + gamma1
                            * (eui - lamda6 * bitems.get(itemid));
                    bitems.put(itemid, tmp);

                    // update user factor and movie factor vectors

                    PreferenceArray ItemFactor = qitems.get(itemid);
                    UserFactor = pusers.get(userid);
                    PreferenceArray puTempFactor = puTemp.get(userid);

                    for (int k = 0; k < parameter_k; k++) {

                        // user factor
                        float preval = UserFactor.getValue(k);
                        float temp = ItemFactor.getValue(k);
                        preval = (float) (preval + gamma2
                                * (eui * temp - lamda7 * preval));
                        UserFactor.setValue(k, preval);

                        // item factor
                        preval = ItemFactor.getValue(k);
                        temp = puTempFactor.getValue(k);
                        preval = (float) (preval + gamma2
                                * (eui * temp - lamda7 * preval));
                        ItemFactor.setValue(k, preval);

                        // Accumulate information for gradient steps on y_i
                        preval = sumQE.getValue(k);
                        preval += eui * ItemFactor.getValue(k);
                        sumQE.setValue(k, preval);

                        // // implicit factor test;
                        // PreferenceArray yFactor = y.get(itemid);
                        // preval = yFactor.getValue(k);
                        // preval += gamma2
                        // * (eui*ItemFactor.getValue(k)/Math.sqrt(nu) - lamda7
                        // * preval);
                        // yFactor.setValue(k, preval);
                    }
                }

                // implicit factor
                itor = tmpitems.iterateNonZero();
                while (itor.hasNext()) {
                    Element e = itor.next();
                    int itemid = e.index();
                    PreferenceArray yFactor = y.get(itemid);
                    for (int k = 0; k < parameter_k; k++) {
                        float preval = yFactor.getValue(k);
                        preval = (float) (preval + gamma2
                                * (sumQE.getValue(k) / Math.sqrt(nu) - lamda7
View Full Code Here
42
43
44
45
46
47
48
49
50
51
 
    public void clearVector(Vector v) {
     
      Iterator<Element> it = v.iterateNonZero();
      while (it.hasNext()) {
        Element e = it.next();
        e.set(0);
      }
     
    }
View Full Code Here
124
125
126
127
128
129
130
131
132
133
   
    public void clearVector(Vector v) {
     
      Iterator<Element> it = v.iterateNonZero();
      while (it.hasNext()) {
        Element e = it.next();
        e.set(0);
      }
     
    }
View Full Code Here
73
74
75
76
77
78
79
80
81
82
83
84
                Iterator<Element> iter = normGamma.iterateNonZero();
                double maxTopicScore = 0.0;
                int idx = 0;
                int topic = 0;
                while(iter.hasNext()) {
                    Element e = iter.next();
                    double score = e.get();
                    if (score > maxTopicScore) {
                        maxTopicScore = score;
                        topic = idx;
                    }
                   
View Full Code Here
94
95
96
97
98
99
100
101
102
103
104
105
                Iterator<Element> iter = normGamma.iterateNonZero();
                double maxTopicScore = 0.0;
                int idx = 0;
                int topic = 0;
                while(iter.hasNext()) {
                    Element e = iter.next();
                    double score = e.get();
                    if (score > maxTopicScore) {
                        maxTopicScore = score;
                        topic = idx;
                    }
                   
View Full Code Here
67
68
69
70
71
72
73
74
75
76
77
78
79
                if (c == null) {
                    c = new Cloud(template);
                }
                Iterator<Element> viter = wvw.getVector().iterateNonZero();
                while (viter.hasNext()) {
                    Element e = viter.next();
                    String feature = invertedFeatureIndex.get(e.index());
                    c.addTag(new Tag(feature, e.get()));
                }
               
                cloudMap.put(clusterId, c);
            }
        } catch (IOException e) {
View Full Code Here
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
            OutputCollector<Text, Text> output, Reporter reporter)
            throws IOException {
        Vector v = value.get();
        StringBuffer buffer = new StringBuffer();
        for (int i = 0; i < v.size(); i++) {
            Element el = v.getElement(i);
            int index = el.index();
            // increment index so that starts at 1
            index++;
            double weight = el.get();
            if (weight != 0)
                buffer.append(" ").append(index).append(":").append(weight);
        }
        String rep = buffer.toString();
        if (rep.length() > 0)
View Full Code Here
317
318
319
320
321
322
323
324
325
326
327
328
329
  protected Tuple toSparseVectorTuple(Vector v) {
    DataBag bag = bagFactory.newDefaultBag();
    Iterator<Element> itr = v.iterateNonZero();
    while (itr.hasNext()) {
      Element e = itr.next();
      bag.add(tupleFactory.newTupleNoCopy(Lists.<Number> newArrayList(e.index(),
          floatPrecision ? (float) e.get() : e.get())));
    }
    return cardinality != null ? tupleFactory.newTupleNoCopy(ImmutableList.of(bag)) : tupleFactory
        .newTupleNoCopy(ImmutableList.of(v.size(),
            bag));
  }
View Full Code Here
TOP

Related Classes of org.apache.mahout.math.Vector.Element

  • com.digitalpebble.behemoth.mahout.util.Mahout2LibSVM
  • com.mozilla.grouperfish.mahout.clustering.display.kmeans.WordCloud
  • com.mozilla.grouperfish.mahout.clustering.display.lda.DisplayLDABase
  • com.mozilla.grouperfish.mahout.clustering.display.lda.OriginalText
  • com.twitter.elephantbird.pig.mahout.VectorWritableConverter
  • org.apache.mahout.classifier.discriminative.WinnowTrainer
  • org.apache.mahout.classifier.naivebayes.AbstractNaiveBayesClassifier
  • org.apache.mahout.classifier.naivebayes.NaiveBayesTestBase
  • org.apache.mahout.classifier.naivebayes.trainer.NaiveBayesThetaComplementaryMapper
  • org.apache.mahout.clustering.CIMapper
    • 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.