List of like() Examples

Examples of like()

ca.weblite.objc.annotations.Msg.like()
cern.colt.matrix.DoubleMatrix1D.like()
Construct and returns a new empty matrix of the same dynamic type as the receiver, having the same size. For example, if the receiver is an instance of type DenseDoubleMatrix1D the new matrix must also be of type DenseDoubleMatrix1D, if the receiver is an instance of type SparseDoubleMatrix1D the new matrix must also be of type SparseDoubleMatrix1D, etc. In general, the new matrix should have internal parametrization as similar as possible. @return a new empty matrix of the same dynamic type.
cern.colt.matrix.DoubleMatrix2D.like()
Construct and returns a new empty matrix of the same dynamic type as the receiver, having the same number of rows and columns. For example, if the receiver is an instance of type DenseDoubleMatrix2D the new matrix must also be of type DenseDoubleMatrix2D, if the receiver is an instance of type SparseDoubleMatrix2D the new matrix must also be of type SparseDoubleMatrix2D, etc. In general, the new matrix should have internal parametrization as similar as possible. @return a new empty matrix of the same dynamic type.
com.Publication.like()
Ajoute un nouvel utilisateur à la liste de celles qui "aime" cette publication.
Si cet utilisateur "n'aime pas" cette publication, ce ne sera plus le cas après un appel à cette méthode @param pseudo Le pseudonyme de l'utilisateur à ajouter @return False si la personne aimait déjà cette publication, True sinon
com.google.code.lightssh.common.dao.SearchCondition.like()
模糊匹配
com.j256.ormlite.stmt.Where.like()
Add a LIKE clause so the column must mach the value using '%' patterns.
com.sissi.context.JIDs.like()
Bare JID的比较 @param jid @return
javax.persistence.criteria.CriteriaBuilder.like()
Create a predicate for testing whether the expression satisfies the given pattern. @param x string expression @param pattern string expression @return like predicate
org.apache.lucene.queries.mlt.MoreLikeThis.like()
Return a query that will return docs like the passed lucene document ID. @param docNum the documentID of the lucene doc to generate the 'More Like This" query for. @return a query that will return docs like the passed lucene document ID.
org.apache.lucene.search.similar.MoreLikeThis.like()
Return a query that will return docs like the passed lucene document ID. @param docNum the documentID of the lucene doc to generate the 'More Like This" query for. @return a query that will return docs like the passed lucene document ID.
org.apache.mahout.math.DenseVector.like()
org.apache.mahout.math.Vector.like()
Return an empty matrix of the same underlying class as the receiver @return a Vector
org.apache.mahout.matrix.DenseVector.like()
org.geotools.filter.FilterFactoryImplNamespaceAware.like()
org.jeecgframework.core.common.hibernate.qbc.CriteriaQuery.like()
设置like(模糊)查询条件 @param keyname @param keyvalue1 @param keyvalue2
org.nuxeo.ecm.rating.api.LikeService.like()
org.opengis.filter.FilterFactory.like()
Character string comparison operator with pattern matching and default wildcards.
org.opengis.filter.FilterFactory2.like()
Character string comparison operator with pattern matching and specified wildcards. @param expr @param pattern @param wildcard @param singleChar @param escape @param matchCase @return

Examples of org.apache.lucene.queries.mlt.MoreLikeThis.like()

        }
        if (sb.length() > 0) sb.append(" ");
        sb.append(s);
      }
      try {
        similar = (BooleanQuery)mlt.like("field", new StringReader(sb.toString()));
      } catch (Exception e) {
        e.printStackTrace();
        errorMsg("FAILED: " + e.getMessage());
        return;
      }

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Examples of org.apache.lucene.queries.mlt.MoreLikeThis.like()

        errorMsg("FAILED: " + e.getMessage());
        return;
      }
    } else {
      try {
        similar = (BooleanQuery)mlt.like(id);
      } catch (Exception e) {
        e.printStackTrace();
        errorMsg("FAILED: " + e.getMessage());
        return;
      }

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Examples of org.apache.lucene.search.similar.MoreLikeThis.like()

    moreLikeThis.setMinTermFreq(1);
    moreLikeThis.setMinDocFreq(1);
    
    //<start id="lucene.examples.mlt.query"/>
    Reader reader = new FileReader(inputPath); //<co id="mlt.query"/>
    Query query = moreLikeThis.like(reader); 


    TopDocs results 
      = indexSearcher.search(query, maxResults); //<co id="mlt.search"/>
    
    HashMap<String, CategoryHits> categoryHash

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Examples of org.apache.lucene.search.similar.MoreLikeThis.like()

    if (minDocFreq >= 0) {
      mlt.setMinDocFreq(minDocFreq);
    }
    mlt.setMaxQueryTerms(maxQueryTerms);
    mlt.setStopWords(stopWords);
    BooleanQuery bq = (BooleanQuery) mlt.like(new StringReader(likeText), fieldName);
    BooleanClause[] clauses = bq.getClauses();
    // make at least half the terms match
    bq.setMinimumNumberShouldMatch((int) (clauses.length * percentTermsToMatch));
    return bq;
  }

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Examples of org.apache.lucene.search.similar.MoreLikeThis.like()

        mlt.setMinWordLen(minWordLen);
        mlt.setMaxWordLen(maxWordLen);
        mlt.setStopWords(stopWords);
        mlt.setBoost(boostTerms);
        mlt.setBoostFactor(boostTermsFactor);
        BooleanQuery bq = (BooleanQuery) mlt.like(new FastStringReader(likeText));
        BooleanClause[] clauses = bq.getClauses();


        bq.setMinimumNumberShouldMatch((int) (clauses.length * percentTermsToMatch));
        return bq;
    }

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Examples of org.apache.mahout.math.DenseVector.like()

  }


  public void testRmultinom1() {
    double[] b = {0.4, 0.6};
    Vector v = new DenseVector(b);
    Vector t = v.like();
    for (int i = 1; i <= 100; i++) {
      Vector multinom = UncommonDistributions.rMultinom(100, v);
      t = t.plus(multinom);
    }
    System.out.println("sum(rMultinom(" + 100 + ", [0.4, 0.6]))/100="

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Examples of org.apache.mahout.math.DenseVector.like()

  }


  public void testRmultinom2() {
    double[] b = {0.1, 0.2, 0.7};
    Vector v = new DenseVector(b);
    Vector t = v.like();
    for (int i = 1; i <= 100; i++) {
      Vector multinom = UncommonDistributions.rMultinom(100, v);
      t = t.plus(multinom);
    }
    System.out.println("sum(rMultinom(" + 100 + ", [ 0.1, 0.2, 0.7 ]))/100="

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Examples of org.apache.mahout.math.DenseVector.like()


  @Test
  public void testRmultinom1() {
    double[] b = {0.4, 0.6};
    Vector v = new DenseVector(b);
    Vector t = v.like();
    for (int i = 1; i <= 100; i++) {
      Vector multinom = UncommonDistributions.rMultinom(100, v);
      t = t.plus(multinom);
    }
    System.out.println("sum(rMultinom(" + 100 + ", [0.4, 0.6]))/100="

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Examples of org.apache.mahout.math.Vector.like()

  @Override
  public Model<VectorWritable>[] sampleFromPrior(int howMany) {
    Model<VectorWritable>[] result = new NormalModel[howMany];
    for (int i = 0; i < howMany; i++) {
      Vector prototype = getModelPrototype().get();
      result[i] = new NormalModel(prototype.like(), 1);
    }
    return result;
  }
  
  @Override

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Examples of org.apache.mahout.math.Vector.like()

  @Override
  public Model<VectorWritable>[] sampleFromPrior(int howMany) {
    Model<VectorWritable>[] result = new L1Model[howMany];
    for (int i = 0; i < howMany; i++) {
      Vector prototype = getModelPrototype().get();
      result[i] = new L1Model(prototype.like());
    }
    return result;
  }
  
  @Override

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