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Example 1 with StabilitySelection

use of edu.cmu.tetrad.algcomparison.algorithm.StabilitySelection in project tetrad by cmu-phil.

the class ExampleStARS method main.

public static void main(String... args) {
    Parameters parameters = new Parameters();
    // parameters.set("numMeasures", 100);
    // parameters.set("avgDegree", 2, 4);
    // parameters.set("sampleSize", 100, 500);
    // parameters.set("numRuns", 5);
    parameters.set("numMeasures", 200);
    parameters.set("avgDegree", 2, 4, 6);
    parameters.set("sampleSize", 100, 500);
    parameters.set("numRuns", 2);
    parameters.set("differentGraphs", true);
    parameters.set("numLatents", 0);
    parameters.set("maxDegree", 100);
    parameters.set("maxIndegree", 100);
    parameters.set("maxOutdegree", 100);
    parameters.set("connected", false);
    parameters.set("coefLow", 0.2);
    parameters.set("coefHigh", 0.9);
    parameters.set("varLow", 1);
    parameters.set("varHigh", 3);
    parameters.set("verbose", false);
    parameters.set("coefSymmetric", true);
    parameters.set("percentDiscrete", 0);
    parameters.set("numCategories", 3);
    parameters.set("differentGraphs", true);
    parameters.set("intervalBetweenShocks", 10);
    parameters.set("intervalBetweenRecordings", 10);
    parameters.set("fisherEpsilon", 0.001);
    parameters.set("randomizeColumns", true);
    parameters.set("alpha", 0.01);
    parameters.set("depth", -1);
    parameters.set("penaltyDiscount", 2);
    parameters.set("useMaxPOrientationHeuristic", false);
    parameters.set("maxPOrientationMaxPathLength", 3);
    parameters.set("verbose", false);
    parameters.set("scaleFreeAlpha", 0.00001);
    parameters.set("scaleFreeBeta", 0.4);
    parameters.set("scaleFreeDeltaIn", .1);
    parameters.set("scaleFreeDeltaOut", 3);
    parameters.set("symmetricFirstStep", false);
    parameters.set("faithfulnessAssumed", true);
    parameters.set("maxDegree", 100);
    parameters.set("StARS.tolerance", .5);
    parameters.set("StARS.cutoff", .05);
    parameters.set("numSubsamples", 7);
    parameters.set("percentSubsampleSize", .5);
    parameters.set("percentStability", .5);
    Statistics statistics = new Statistics();
    statistics.add(new ParameterColumn("numMeasures"));
    statistics.add(new ParameterColumn("avgDegree"));
    statistics.add(new ParameterColumn("sampleSize"));
    statistics.add(new AdjacencyPrecision());
    statistics.add(new AdjacencyRecall());
    statistics.add(new ArrowheadPrecision());
    statistics.add(new ArrowheadRecall());
    statistics.add(new ElapsedTime());
    statistics.setWeight("AP", 0.25);
    statistics.setWeight("AR", 0.25);
    statistics.setWeight("AHP", 0.25);
    statistics.setWeight("AHR", 0.25);
    Algorithms algorithms = new Algorithms();
    parameters.set("logScale", false);
    algorithms.add(new StabilitySelection(new Fges(new SemBicScore())));
    algorithms.add(new StARS(new Fges(new SemBicScore()), "penaltyDiscount", 1, 5));
    algorithms.add(new FirstInflection(new Fges(new SemBicScore()), "penaltyDiscount", 1, 5, .1));
    // parameters.set("penaltyDiscount", 5, 11, 15);
    // algorithms.add(new Fges(new SemBicScore()));
    // parameters.set("logScale", true);
    // Algorithm fges = new Fges(new FisherZScore());
    // algorithms.add(new StARS(fges, "alpha", -10, -2, -8));
    // algorithms.add(new FirstInflection(fges, "alpha", -10, -2, -3));
    Simulations simulations = new Simulations();
    simulations.add(new LinearFisherModel(new RandomForward()));
    Comparison comparison = new Comparison();
    comparison.setShowAlgorithmIndices(true);
    comparison.setShowSimulationIndices(true);
    comparison.setSortByUtility(false);
    comparison.setShowUtilities(false);
    comparison.setParallelized(true);
    comparison.setComparisonGraph(Comparison.ComparisonGraph.Pattern_of_the_true_DAG);
    comparison.compareFromSimulations("first.inflection", simulations, algorithms, statistics, parameters);
}
Also used : Simulations(edu.cmu.tetrad.algcomparison.simulation.Simulations) Parameters(edu.cmu.tetrad.util.Parameters) LinearFisherModel(edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel) StabilitySelection(edu.cmu.tetrad.algcomparison.algorithm.StabilitySelection) StARS(edu.cmu.tetrad.algcomparison.algorithm.StARS) RandomForward(edu.cmu.tetrad.algcomparison.graph.RandomForward) Fges(edu.cmu.tetrad.algcomparison.algorithm.oracle.pattern.Fges) Algorithms(edu.cmu.tetrad.algcomparison.algorithm.Algorithms) Comparison(edu.cmu.tetrad.algcomparison.Comparison) SemBicScore(edu.cmu.tetrad.algcomparison.score.SemBicScore) FirstInflection(edu.cmu.tetrad.algcomparison.algorithm.FirstInflection)

Aggregations

Comparison (edu.cmu.tetrad.algcomparison.Comparison)1 Algorithms (edu.cmu.tetrad.algcomparison.algorithm.Algorithms)1 FirstInflection (edu.cmu.tetrad.algcomparison.algorithm.FirstInflection)1 StARS (edu.cmu.tetrad.algcomparison.algorithm.StARS)1 StabilitySelection (edu.cmu.tetrad.algcomparison.algorithm.StabilitySelection)1 Fges (edu.cmu.tetrad.algcomparison.algorithm.oracle.pattern.Fges)1 RandomForward (edu.cmu.tetrad.algcomparison.graph.RandomForward)1 SemBicScore (edu.cmu.tetrad.algcomparison.score.SemBicScore)1 LinearFisherModel (edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel)1 Simulations (edu.cmu.tetrad.algcomparison.simulation.Simulations)1 Parameters (edu.cmu.tetrad.util.Parameters)1