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scalation.graph_db

BoundedTreeWidthBN

class BoundedTreeWidthBN extends Error

The BoundedTreeWidthBN class provides bounded treewidth Bayesian Networks.

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Instance Constructors

  1. new BoundedTreeWidthBN(g_in: MGraph[Double], kMax: Int)

    g_in

    the input directed graph (FIX: training data)

    kMax

    the maximum allowed treewidth

Value Members

  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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  3. final def ==(arg0: Any): Boolean
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  4. val DEBUG: Boolean
  5. def addEdgesGreedily(g: MGraph[Double], mp: MGraph[Double], k: Int): Unit

    Greedily add edges to 'g' that do not increase treewidth beyond 'kMax'.

    Greedily add edges to 'g' that do not increase treewidth beyond 'kMax'.

    g

    the maximum scoring graph of bounded treewidth

    mp

    the triangulated moralized graph

    k

    the current treewidth

  6. final def asInstanceOf[T0]: T0
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  7. def blockSort(mp: MGraph[Double]): Array[Int]

    Order the blocks in the graph.

    Order the blocks in the graph.

    mp

    the triangulated moralized graph

  8. def clone(): AnyRef
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  9. final def eq(arg0: AnyRef): Boolean
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  10. def equals(arg0: Any): Boolean
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  11. def findbestEdge(g: MGraph[Double], mp: MGraph[Double], k: Int): Pair

    Find and return the next best remaining edge.

    Find and return the next best remaining edge. Return (-1, -1) if there are none.

    g

    the maximum scoring graph of bounded treewidth

    mp

    the triangulated moralized graph

    k

    the current treewidth

  12. final def flaw(method: String, message: String): Unit
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  13. final def getClass(): Class[_]
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  14. def hashCode(): Int
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  15. final def isInstanceOf[T0]: Boolean
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  16. def learnBN(): MGraph[Double]

    Learn a Bayesian Network with Bounded Treewidth.

    Learn a Bayesian Network with Bounded Treewidth. Starting with a spanning tree, add score improving edges, so long as the 'kMax' bound on the graph's treewidth is not exceeded. This corresponds to Algorithm 1 in the paper.

  17. def maxCliqueSize(mp: MGraph[Double]): Int

    Compute the size of the largest clique in the graph.

    Compute the size of the largest clique in the graph.

    mp

    the triangulated moralized graph whose maximum clique size is sought

  18. final def ne(arg0: AnyRef): Boolean
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  19. final def notify(): Unit
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  20. final def notifyAll(): Unit
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  21. def orderVertices(g: MGraph[Double], mp: MGraph[Double]): (Array[Int], Array[Int])

    Order the vertices and blocks in the graph.

    Order the vertices and blocks in the graph.

    g

    the graph built up from the spanning tree

    mp

    the triangulated moralized graph

    See also

    Algorithm 7

  22. def positiveEdges: Boolean

    Determine whether positive scoring edges still exist.

  23. val stree: MinSpanningTree
  24. final def synchronized[T0](arg0: ⇒ T0): T0
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  25. def toString(): String
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  26. final def wait(arg0: Long, arg1: Int): Unit
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  27. final def wait(arg0: Long): Unit
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  28. final def wait(): Unit
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  1. def finalize(): Unit
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