Package | Description |
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oracle.pgx.api |
This package contains the main Java APIs.
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Modifier and Type | Method and Description |
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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)
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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)
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BipartiteGraph |
PgxGraph.bipartiteSubGraphFromLeftSet(java.util.Collection<VertexProperty<?,?>> vertexProps, java.util.Collection<EdgeProperty<?>> edgeProps, VertexSet<?> vertexSet, java.lang.String newGraphName, java.lang.String isLeftPropName)
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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 |
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PgxFuture<BipartiteGraph> |
PgxGraph.bipartiteSubGraphFromInDegreeAsync()
Create a bipartite version of this graph with all vertices of in-degree = 0 being the left set.
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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.
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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.
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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.
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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.
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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.
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PgxFuture<BipartiteGraph> |
PgxGraph.bipartiteSubGraphFromLeftSetAsync(VertexSet<?> vertexSet)
Create a bipartite version of this graph with the given vertex set being the left set.
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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.
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Modifier and Type | Method and Description |
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<ID> MatrixFactorizationModel<ID> |
Analyst.matrixFactorizationGradientDescent(BipartiteGraph graph, EdgeProperty<java.lang.Double> weight)
Matrix factorization can be used as a recommendation algorithm for bipartite graphs
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<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
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<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
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<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
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<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
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<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
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<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
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<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
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<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
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<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
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<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<ID, Double>) 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.
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<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.
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<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.
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<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.
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<ID> VertexProperty<ID,java.lang.Double> |
Analyst.personalizedSalsa(BipartiteGraph graph, VertexSet<ID> vertices)
Personalized salsa for a set of vertices of interest.
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<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.
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<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.
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<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.
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<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.personalizedSalsaAsync(BipartiteGraph graph, PgxVertex<ID> v)
Personalized salsa for a vertex of interest.
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<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.
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<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.
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<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.
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<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.personalizedSalsaAsync(BipartiteGraph graph, VertexSet<ID> vertices)
Personalized salsa for a set of vertices of interest.
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<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.
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<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.
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<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.
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<ID> VertexProperty<ID,java.lang.Double> |
Analyst.salsa(BipartiteGraph graph)
SALSA computes ranking scores.
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<ID> VertexProperty<ID,java.lang.Double> |
Analyst.salsa(BipartiteGraph graph, double maxDiff, int maxIter)
SALSA computes ranking scores.
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<ID> VertexProperty<ID,java.lang.Double> |
Analyst.salsa(BipartiteGraph graph, double maxDiff, int maxIter, VertexProperty<ID,java.lang.Double> salsaRank)
SALSA computes ranking scores.
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<ID> VertexProperty<ID,java.lang.Double> |
Analyst.salsa(BipartiteGraph graph, VertexProperty<ID,java.lang.Double> salsaRank)
SALSA computes ranking scores.
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<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.salsaAsync(BipartiteGraph graph)
SALSA computes ranking scores.
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<ID> PgxFuture<VertexProperty<ID,java.lang.Double>> |
Analyst.salsaAsync(BipartiteGraph graph, double maxDiff, int maxIter)
SALSA computes ranking scores.
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<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.
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<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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