Package | Description |
---|---|
oracle.pgx.api |
This package contains the main Java APIs.
|
Modifier and Type | Method and Description |
---|---|
BipartiteGraph |
PgxGraph.bipartiteSubGraphFromInDegree()
Blocking version of
PgxGraph.bipartiteSubGraphFromInDegreeAsync() . |
BipartiteGraph |
PgxGraph.bipartiteSubGraphFromInDegree(java.util.Collection<VertexProperty<?,?>> vertexProps,
java.util.Collection<EdgeProperty<?>> edgeProps,
java.lang.String newGraphName)
Blocking version of
PgxGraph.bipartiteSubGraphFromInDegreeAsync(Collection, Collection, String) . |
BipartiteGraph |
PgxGraph.bipartiteSubGraphFromInDegree(java.util.Collection<VertexProperty<?,?>> vertexProps,
java.util.Collection<EdgeProperty<?>> edgeProps,
java.lang.String newGraphName,
java.lang.String isLeftPropName,
boolean inPlace)
|
BipartiteGraph |
PgxGraph.bipartiteSubGraphFromInDegree(java.lang.String newGraphName)
Blocking version of
PgxGraph.bipartiteSubGraphFromInDegreeAsync(String) . |
BipartiteGraph |
PgxGraph.bipartiteSubGraphFromLeftSet(java.util.Collection<VertexProperty<?,?>> vertexProps,
java.util.Collection<EdgeProperty<?>> edgeProps,
VertexSet<?> vertexSet,
java.lang.String newGraphName)
|
BipartiteGraph |
PgxGraph.bipartiteSubGraphFromLeftSet(java.util.Collection<VertexProperty<?,?>> vertexProps,
java.util.Collection<EdgeProperty<?>> edgeProps,
VertexSet<?> vertexSet,
java.lang.String newGraphName,
java.lang.String isLeftPropName)
|
BipartiteGraph |
PgxGraph.bipartiteSubGraphFromLeftSet(VertexSet<?> vertexSet)
Blocking version of
PgxGraph.bipartiteSubGraphFromLeftSetAsync(VertexSet) . |
BipartiteGraph |
PgxGraph.bipartiteSubGraphFromLeftSet(VertexSet<?> vertexSet,
java.lang.String newGraphName)
Blocking version of
PgxGraph.bipartiteSubGraphFromLeftSetAsync(VertexSet, String) . |
Modifier and Type | Method and Description |
---|---|
PgxFuture<BipartiteGraph> |
PgxGraph.bipartiteSubGraphFromInDegreeAsync()
Create a bipartite version of this graph with all vertices of in-degree = 0 being the left set.
|
PgxFuture<BipartiteGraph> |
PgxGraph.bipartiteSubGraphFromInDegreeAsync(java.util.Collection<VertexProperty<?,?>> vertexProps,
java.util.Collection<EdgeProperty<?>> edgeProps,
java.lang.String newGraphName)
Create a bipartite version of this graph with all vertices of in-degree = 0 being the left set.
|
PgxFuture<BipartiteGraph> |
PgxGraph.bipartiteSubGraphFromInDegreeAsync(java.util.Collection<VertexProperty<?,?>> vertexProps,
java.util.Collection<EdgeProperty<?>> edgeProps,
java.lang.String newGraphName,
java.lang.String isLeftPropName,
boolean inPlace)
Create a bipartite version of this graph with all vertices of in-degree = 0 being the left set.
|
PgxFuture<BipartiteGraph> |
PgxGraph.bipartiteSubGraphFromInDegreeAsync(java.lang.String newGraphName)
Create a bipartite version of this graph with all vertices of in-degree = 0 being the left set.
|
PgxFuture<BipartiteGraph> |
PgxGraph.bipartiteSubGraphFromLeftSetAsync(java.util.Collection<VertexProperty<?,?>> vertexProps,
java.util.Collection<EdgeProperty<?>> edgeProps,
VertexSet<?> vertexSet,
java.lang.String newGraphName)
Create a bipartite version of this graph with the given vertex set being the left set.
|
PgxFuture<BipartiteGraph> |
PgxGraph.bipartiteSubGraphFromLeftSetAsync(java.util.Collection<VertexProperty<?,?>> vertexProps,
java.util.Collection<EdgeProperty<?>> edgeProps,
VertexSet<?> vertexSet,
java.lang.String newGraphName,
java.lang.String isLeftPropName)
Create a bipartite version of this graph with the given vertex set being the left set.
|
PgxFuture<BipartiteGraph> |
PgxGraph.bipartiteSubGraphFromLeftSetAsync(VertexSet<?> vertexSet)
Create a bipartite version of this graph with the given vertex set being the left set.
|
PgxFuture<BipartiteGraph> |
PgxGraph.bipartiteSubGraphFromLeftSetAsync(VertexSet<?> vertexSet,
java.lang.String newGraphName)
Create a bipartite version of this graph with the given vertex set being the left set.
|
Modifier and Type | Method and Description |
---|---|
<ID> MatrixFactorizationModel<ID> |
Analyst.matrixFactorizationGradientDescent(BipartiteGraph graph,
EdgeProperty<java.lang.Double> weight)
Matrix factorization can be used as a recommendation algorithm for bipartite graphs
|
<ID> MatrixFactorizationModel<ID> |
Analyst.matrixFactorizationGradientDescent(BipartiteGraph graph,
EdgeProperty<java.lang.Double> weight,
double learningRate,
double changePerStep,
double lambda,
int maxStep,
int vectorLength)
Matrix factorization can be used as a recommendation algorithm for bipartite graphs
|
<ID> MatrixFactorizationModel<ID> |
Analyst.matrixFactorizationGradientDescent(BipartiteGraph graph,
EdgeProperty<java.lang.Double> weight,
double learningRate,
double changePerStep,
double lambda,
int maxStep,
int vectorLength,
VertexProperty<ID,PgxVect<java.lang.Double>> features)
Matrix factorization can be used as a recommendation algorithm for bipartite graphs
|
<ID> MatrixFactorizationModel<ID> |
Analyst.matrixFactorizationGradientDescent(BipartiteGraph graph,
EdgeProperty<java.lang.Double> weight,
VertexProperty<ID,PgxVect<java.lang.Double>> features)
Matrix factorization can be used as a recommendation algorithm for bipartite graphs
|
<ID> PgxFuture<MatrixFactorizationModel<ID>> |
Analyst.matrixFactorizationGradientDescentAsync(BipartiteGraph graph,
EdgeProperty<java.lang.Double> weight)
Matrix factorization can be used as a recommendation algorithm for bipartite graphs
|
<ID> PgxFuture<MatrixFactorizationModel<ID>> |
Analyst.matrixFactorizationGradientDescentAsync(BipartiteGraph graph,
EdgeProperty<java.lang.Double> weight,
double learningRate,
double changePerStep,
double lambda,
int maxStep,
int vectorLength)
Matrix factorization can be used as a recommendation algorithm for bipartite graphs
|
<ID> PgxFuture<MatrixFactorizationModel<ID>> |
Analyst.matrixFactorizationGradientDescentAsync(BipartiteGraph graph,
EdgeProperty<java.lang.Double> weight,
double learningRate,
double changePerStep,
double lambda,
int maxStep,
int vectorLength,
VertexProperty<ID,PgxVect<java.lang.Double>> features)
Matrix factorization can be used as a recommendation algorithm for bipartite graphs
|
<ID> PgxFuture<MatrixFactorizationModel<ID>> |
Analyst.matrixFactorizationGradientDescentAsync(BipartiteGraph graph,
EdgeProperty<java.lang.Double> weight,
VertexProperty<ID,PgxVect<java.lang.Double>> features)
Matrix factorization can be used as a recommendation algorithm for bipartite graphs
|
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.matrixFactorizationRecommendations(BipartiteGraph graph,
ID user,
int vectorLength,
VertexProperty<ID,PgxVect<java.lang.Double>> feature,
VertexProperty<ID,java.lang.Double> estimatedRating)
Convenience wrapper around
Analyst.matrixFactorizationRecommendations(BipartiteGraph, PgxVertex, int,
VertexProperty, VertexProperty) taking a vertex ID instead of a PgxVertex . |
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.matrixFactorizationRecommendations(BipartiteGraph graph,
PgxVertex<ID> user,
int vectorLength,
VertexProperty<ID,PgxVect<java.lang.Double>> feature,
VertexProperty<ID,java.lang.Double> estimatedRating)
Estimate rating can be used as a prediction algorithm for bipartite graphs
|
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.matrixFactorizationRecommendationsAsync(BipartiteGraph graph,
PgxVertex<ID> user,
int vectorLength,
VertexProperty<ID,PgxVect<java.lang.Double>> feature,
VertexProperty<ID,java.lang.Double> estimatedRating)
Estimate rating can be used as a prediction algorithm for bipartite graphs
|
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.personalizedSalsa(BipartiteGraph graph,
ID v,
java.math.BigDecimal d,
int maxIterations,
java.math.BigDecimal maxDiff)
Convenience wrapper around
Analyst.personalizedSalsa(BipartiteGraph, PgxVertex, BigDecimal, int, BigDecimal)
taking a vertex ID instead of PgxVertex . |
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.personalizedSalsa(BipartiteGraph graph,
ID v,
java.math.BigDecimal d,
int maxIterations,
java.math.BigDecimal maxDiff,
VertexProperty<ID,java.lang.Double> salsaRank)
Convenience wrapper around
#personalizedSalsa(BipartiteGraph, PgxVertex, BigDecimal, int, BigDecimal, VertexProperty
taking a vertex ID instead of PgxVertex . |
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.personalizedSalsa(BipartiteGraph graph,
PgxVertex<ID> v)
Personalized salsa for a vertex of interest.
|
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.personalizedSalsa(BipartiteGraph graph,
PgxVertex<ID> v,
double d,
int maxIter,
double maxDiff)
Personalized salsa for a vertex of interest.
|
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.personalizedSalsa(BipartiteGraph graph,
PgxVertex<ID> v,
double d,
int maxIter,
double maxDiff,
VertexProperty<ID,java.lang.Double> salsaRank)
Personalized salsa for a vertex of interest.
|
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.personalizedSalsa(BipartiteGraph graph,
PgxVertex<ID> v,
VertexProperty<ID,java.lang.Double> salsaRank)
Personalized salsa for a vertex of interest.
|
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.personalizedSalsa(BipartiteGraph graph,
VertexSet<ID> vertices)
Personalized salsa for a set of vertices of interest.
|
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.personalizedSalsa(BipartiteGraph graph,
VertexSet<ID> vertices,
double d,
int maxIter,
double maxDiff)
Personalized salsa for a set of vertices of interest.
|
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.personalizedSalsa(BipartiteGraph graph,
VertexSet<ID> vertices,
double d,
int maxIter,
double maxDiff,
VertexProperty<ID,java.lang.Double> salsaRank)
Personalized salsa for a set of vertices of interest.
|
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.personalizedSalsa(BipartiteGraph graph,
VertexSet<ID> vertices,
VertexProperty<ID,java.lang.Double> salsaRank)
Personalized salsa for a set of vertices of interest.
|
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.personalizedSalsaAsync(BipartiteGraph graph,
PgxVertex<ID> v)
Personalized salsa for a vertex of interest.
|
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.personalizedSalsaAsync(BipartiteGraph graph,
PgxVertex<ID> v,
double d,
int maxIter,
double maxDiff)
Personalized salsa for a vertex of interest.
|
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.personalizedSalsaAsync(BipartiteGraph graph,
PgxVertex<ID> v,
double d,
int maxIter,
double maxDiff,
VertexProperty<ID,java.lang.Double> salsaRank)
Personalized salsa for a vertex of interest.
|
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.personalizedSalsaAsync(BipartiteGraph graph,
PgxVertex<ID> v,
VertexProperty<ID,java.lang.Double> salsaRank)
Personalized salsa for a vertex of interest.
|
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.personalizedSalsaAsync(BipartiteGraph graph,
VertexSet<ID> vertices)
Personalized salsa for a set of vertices of interest.
|
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.personalizedSalsaAsync(BipartiteGraph graph,
VertexSet<ID> vertices,
double d,
int maxIter,
double maxDiff)
Personalized salsa for a set of vertices of interest.
|
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.personalizedSalsaAsync(BipartiteGraph graph,
VertexSet<ID> vertices,
double d,
int maxIter,
double maxDiff,
VertexProperty<ID,java.lang.Double> salsaRank)
Personalized salsa for a set of vertices of interest.
|
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.personalizedSalsaAsync(BipartiteGraph graph,
VertexSet<ID> vertices,
VertexProperty<ID,java.lang.Double> salsaRank)
Personalized salsa for a set of vertices of interest.
|
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.salsa(BipartiteGraph graph)
SALSA computes ranking scores.
|
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.salsa(BipartiteGraph graph,
double maxDiff,
int maxIter)
SALSA computes ranking scores.
|
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.salsa(BipartiteGraph graph,
double maxDiff,
int maxIter,
VertexProperty<ID,java.lang.Double> salsaRank)
SALSA computes ranking scores.
|
<ID> Pair<VertexSequence<ID>,VertexSequence<ID>> |
Analyst.salsa(BipartiteGraph graph,
int k)
Deprecated.
since 2.7.0 - use
Analyst.salsa(BipartiteGraph) instead |
<ID> Pair<VertexSequence<ID>,VertexSequence<ID>> |
Analyst.salsa(BipartiteGraph graph,
int k,
double maxDiff,
double d,
int maxIter)
Deprecated.
since 2.7.0 - use
Analyst.salsa(BipartiteGraph, double, int) instead |
<ID> VertexProperty<ID,java.lang.Double> |
Analyst.salsa(BipartiteGraph graph,
VertexProperty<ID,java.lang.Double> salsaRank)
SALSA computes ranking scores.
|
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.salsaAsync(BipartiteGraph graph)
SALSA computes ranking scores.
|
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.salsaAsync(BipartiteGraph graph,
double maxDiff,
int maxIter)
SALSA computes ranking scores.
|
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.salsaAsync(BipartiteGraph graph,
double maxDiff,
int maxIter,
VertexProperty<ID,java.lang.Double> salsaRank)
SALSA computes ranking scores.
|
<ID> PgxFuture<Pair<VertexSequence<ID>,VertexSequence<ID>>> |
Analyst.salsaAsync(BipartiteGraph graph,
int k)
Deprecated.
since 2.7.0 - use
Analyst.salsaAsync(BipartiteGraph) instead |
<ID> PgxFuture<Pair<VertexSequence<ID>,VertexSequence<ID>>> |
Analyst.salsaAsync(BipartiteGraph graph,
int k,
double maxDiff,
double d,
int maxIter)
Deprecated.
since 2.7.0 - use
Analyst.salsaAsync(BipartiteGraph, double, int) instead |
<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.salsaAsync(BipartiteGraph graph,
VertexProperty<ID,java.lang.Double> salsaRank)
SALSA computes ranking scores.
|
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