Examples of cascading.pattern.model.tree.Tree

cascading.pattern.model.tree.Tree
Class Tree defines a decision tree.
A Tree is literally a tree data structure where every possible branch is governed by a predicate, when traversed, a branch is chosen if the predicate returns true against the current {@link cascading.tuple.Tuple}.
When a leaf node is reached the "score" is returned, where the score can be a category or numeric value.
When a set of Tree instances should be applied, see {@link cascading.pattern.ensemble.ParallelEnsembleAssembly}for constructing a random forest implementation.


  private Pipe handleTreeModel( Pipe tail, TreeModel model )
    {
    ModelSchema modelSchema = createModelSchema( model );


    Tree tree = createTree( model, modelSchema );


    TreeSpec treeSpec = new TreeSpec( modelSchema, tree );


    return create( tail, modelSchema, new TreeFunction( treeSpec ) );
    }

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  {
  public static Tree createTree( TreeModel model, ModelSchema modelSchema )
    {
    Node parent = model.getNode();


    Tree tree = new Tree( parent.getId() );


    buildTree( modelSchema, tree, parent );


    return tree;
    }

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    ensembleSpec.setSelectionStrategy( new MajorityVote() );


    {
    TreeSpec treeSpec = new TreeSpec( modelSchema );


    Tree tree = new Tree( "1" );


    tree.addPredicate( "1", "2", new LessOrEqualThanPredicate( "var0", 0.5d ) );
    tree.addPredicate( "2", "4", new LessOrEqualThanPredicate( "var2", 0.5d ), "1" );
    tree.addPredicate( "2", "5", new GreaterThanPredicate( "var2", 0.5d ), "0" );
    tree.addPredicate( "1", "3", new GreaterThanPredicate( "var0", 0.5d ) );
    tree.addPredicate( "3", "6", new LessOrEqualThanPredicate( "var1", 0.5d ), "0" );
    tree.addPredicate( "3", "7", new GreaterThanPredicate( "var1", 0.5d ), "1" );


    treeSpec.setTree( tree );


    ensembleSpec.addModelSpec( treeSpec );
    }


    {
    TreeSpec treeSpec = new TreeSpec( modelSchema );


    Tree tree = new Tree( "1" );


    tree.addPredicate( "1", "2", new LessOrEqualThanPredicate( "var1", 0.5d ), "1" );
    tree.addPredicate( "1", "3", new GreaterThanPredicate( "var1", 0.5d ), "0" );


    treeSpec.setTree( tree );


    ensembleSpec.addModelSpec( treeSpec );
    }


    {
    TreeSpec treeSpec = new TreeSpec( modelSchema );


    Tree tree = new Tree( "1" );


    tree.addPredicate( "1", "2", new LessOrEqualThanPredicate( "var0", 0.5d ), "1" );
    tree.addPredicate( "1", "3", new GreaterThanPredicate( "var0", 0.5d ), "0" );


    treeSpec.setTree( tree );


    ensembleSpec.addModelSpec( treeSpec );
    }

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    ensembleSpec.setSelectionStrategy( new Average() );


    {
    TreeSpec treeSpec = new TreeSpec( modelSchema );


    Tree tree = new Tree( "1" );


    tree.addPredicate( "1", "2", new LessOrEqualThanPredicate( "var0", 0.5d ) );
    tree.addPredicate( "2", "4", new LessOrEqualThanPredicate( "var2", 0.5d ), 1 );
    tree.addPredicate( "2", "5", new GreaterThanPredicate( "var2", 0.5d ), 0 );
    tree.addPredicate( "1", "3", new GreaterThanPredicate( "var0", 0.5d ) );
    tree.addPredicate( "3", "6", new LessOrEqualThanPredicate( "var1", 0.5d ), 0 );
    tree.addPredicate( "3", "7", new GreaterThanPredicate( "var1", 0.5d ), 1 );


    treeSpec.setTree( tree );


    ensembleSpec.addModelSpec( treeSpec );
    }


    {
    TreeSpec treeSpec = new TreeSpec( modelSchema );


    Tree tree = new Tree( "1" );


    tree.addPredicate( "1", "2", new LessOrEqualThanPredicate( "var1", 0.5d ), 1 );
    tree.addPredicate( "1", "3", new GreaterThanPredicate( "var1", 0.5d ), 0 );


    treeSpec.setTree( tree );


    ensembleSpec.addModelSpec( treeSpec );
    }


    {
    TreeSpec treeSpec = new TreeSpec( modelSchema );


    Tree tree = new Tree( "1" );


    tree.addPredicate( "1", "2", new LessOrEqualThanPredicate( "var0", 0.5d ), 1 );
    tree.addPredicate( "1", "3", new GreaterThanPredicate( "var0", 0.5d ), 0 );


    treeSpec.setTree( tree );


    ensembleSpec.addModelSpec( treeSpec );
    }

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    ModelSchema modelSchema = new ModelSchema( expectedFields, predictedFields );


    TreeSpec treeSpec = new TreeSpec( modelSchema );


    Tree tree = new Tree( "1" );


    tree.addPredicate( "1", "2", new LessOrEqualThanPredicate( "var0", 0.5d ) );
    tree.addPredicate( "2", "4", new LessOrEqualThanPredicate( "var2", 0.5d ), "1" );
    tree.addPredicate( "2", "5", new GreaterThanPredicate( "var2", 0.5d ), "0" );
    tree.addPredicate( "1", "3", new GreaterThanPredicate( "var0", 0.5d ) );
    tree.addPredicate( "3", "6", new LessOrEqualThanPredicate( "var1", 0.5d ), "0" );
    tree.addPredicate( "3", "7", new GreaterThanPredicate( "var1", 0.5d ), "1" );


    treeSpec.setTree( tree );


    TreeFunction treeFunction = new TreeFunction( treeSpec );

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Related Classes of cascading.pattern.model.tree.Tree

cascading.pattern.ensemble.SimpleEnsemblePlatformTest

cascading.pattern.model.ModelTest

cascading.pattern.model.tree.decision.DecisionTree

cascading.pattern.pmml.PMMLPlanner

cascading.pattern.pmml.TreeUtil

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