Package de.lmu.ifi.dbs.elki.data

Examples of de.lmu.ifi.dbs.elki.data.SparseFloatVector$Parameterizer

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    for(int d = selectedAttributes.nextSetBit(0); d >= 0; d = selectedAttributes.nextSetBit(d + 1)) {
      if(v.getValue(d + 1) != 0.0f) {
        values.put(d, v.getValue(d + 1));
      }
    }
    SparseFloatVector projectedVector = new SparseFloatVector(values, selectedAttributes.cardinality());
    return projectedVector;
  }
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  }

  @Override
  protected SimpleTypeInformation<? super SparseFloatVector> convertedType(SimpleTypeInformation<SparseFloatVector> in) {
    final Map<Integer, Float> emptyMap = Collections.emptyMap();
    return new VectorFieldTypeInformation<SparseFloatVector>(SparseFloatVector.class, k, new SparseFloatVector(emptyMap, k));
  }
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    for(int d = selectedAttributes.nextSetBit(0); d >= 0; d = selectedAttributes.nextSetBit(d + 1)) {
      if(v.getValue(d + 1) != 0.0f) {
        values.put(d, v.getValue(d + 1));
      }
    }
    SparseFloatVector projectedVector = new SparseFloatVector(values, selectedAttributes.cardinality());
    return projectedVector;
  }
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    BitSet b = featureVector.getNotNullMask();
    TIntFloatHashMap vals = new TIntFloatHashMap();
    for(int i = b.nextSetBit(0); i >= 0; i = b.nextSetBit(i + 1)) {
      vals.put(i, (float) (featureVector.doubleValue(i) * idf.get(i)));
    }
    return new SparseFloatVector(vals, featureVector.getDimensionality());
  }
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    BitSet b = featureVector.getNotNullMask();
    TIntFloatHashMap vals = new TIntFloatHashMap();
    for(int i = b.nextSetBit(0); i >= 0; i = b.nextSetBit(i + 1)) {
      vals.put(i, (float) (featureVector.doubleValue(i) / idf.get(i)));
    }
    return new SparseFloatVector(vals, featureVector.getDimensionality());
  }
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    }
    TIntFloatHashMap vals = new TIntFloatHashMap();
    for(int i = b.nextSetBit(0); i >= 0; i = b.nextSetBit(i + 1)) {
      vals.put(i, (float) (featureVector.doubleValue(i) / sum * idf.get(i)));
    }
    return new SparseFloatVector(vals, featureVector.getDimensionality());
  }
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    }
    if(curterm != null) {
      labels.add(curterm);
    }

    return new Pair<SparseFloatVector, LabelList>(new SparseFloatVector(values, maxdim), labels);
  }
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  }

  @Override
  protected VectorFieldTypeInformation<SparseFloatVector> getTypeInformation(int dimensionality) {
    final Map<Integer, Float> emptyMap = Collections.emptyMap();
    return new VectorFieldTypeInformation<SparseFloatVector>(SparseFloatVector.class, dimensionality, new SparseFloatVector(emptyMap, dimensionality));
  }
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    }
    Map<Integer, Float> vals = new HashMap<Integer, Float>();
    for(int i = b.nextSetBit(0); i >= 0; i = b.nextSetBit(i + 1)) {
      vals.put(i, (float) (featureVector.doubleValue(i) / sum * idf.get(i).doubleValue()));
    }
    return new SparseFloatVector(vals, featureVector.getDimensionality());
  }
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  }

  @Override
  protected SimpleTypeInformation<? super SparseFloatVector> convertedType(SimpleTypeInformation<SparseFloatVector> in) {
    initializeRandomAttributes(in);
    return new VectorFieldTypeInformation<SparseFloatVector>(SparseFloatVector.class, k, new SparseFloatVector(SparseFloatVector.EMPTYMAP, k));
  }
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Related Classes of de.lmu.ifi.dbs.elki.data.SparseFloatVector$Parameterizer

  • de.lmu.ifi.dbs.elki.datasource.filter.InverseDocumentFrequencyNormalization
  • de.lmu.ifi.dbs.elki.datasource.filter.normalization.InverseDocumentFrequencyNormalization
  • de.lmu.ifi.dbs.elki.datasource.filter.normalization.TFIDFNormalization
  • de.lmu.ifi.dbs.elki.datasource.filter.SparseFloatVectorProjectionFilter
  • de.lmu.ifi.dbs.elki.datasource.filter.SparseFloatVectorRandomProjectionFilter
  • de.lmu.ifi.dbs.elki.datasource.filter.TFIDFNormalization
  • de.lmu.ifi.dbs.elki.datasource.parser.ArffParser
  • de.lmu.ifi.dbs.elki.datasource.parser.SparseFloatVectorLabelParser
  • de.lmu.ifi.dbs.elki.datasource.parser.TermFrequencyParser
  • de.lmu.ifi.dbs.elki.distance.distancevalue.DoubleDistance
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