/** * {@inheritDoc} */ @Override public BayesianNetwork getLearntBayesianNetwork() { //Normalize the sufficient statistics SufficientStatistics normalizedSS = efBayesianNetwork.createZeroSufficientStatistics(); normalizedSS.copy(sumSS); normalizedSS.divideBy(numInstances); efBayesianNetwork.setMomentParameters(normalizedSS); return efBayesianNetwork.toBayesianNetwork(dag); }
/** * {@inheritDoc} */ @Override public BayesianNetwork getLearntBayesianNetwork() { //Normalize the sufficient statistics SufficientStatistics normalizedSS = efBayesianNetwork.createZeroSufficientStatistics(); normalizedSS.copy(sumSS); normalizedSS.divideBy(numInstances); efBayesianNetwork.setMomentParameters(normalizedSS); return efBayesianNetwork.toBayesianNetwork(dag); }
/** * {@inheritDoc} */ @Override public BayesianNetwork getLearntBayesianNetwork() { //Normalize the sufficient statistics SufficientStatistics normalizedSS = efBayesianNetwork.createZeroSufficientStatistics(); normalizedSS.copy(sumSS); normalizedSS.divideBy(numInstances); efBayesianNetwork.setMomentParameters(normalizedSS); return efBayesianNetwork.toBayesianNetwork(dag); }
/** * {@inheritDoc} */ @Override public void updateNaturalFromMomentParameters() { DynamiceBNCompoundVector globalMomentsParam = (DynamiceBNCompoundVector)this.momentParameters; DynamiceBNCompoundVector vectorNatural = this.createEmtpyCompoundVector(); globalMomentsParam.getVectorTime0().divideBy(globalMomentsParam.getIndicatorTime0()); globalMomentsParam.getVectorTimeT().divideBy(globalMomentsParam.getIndicatorTimeT()); this.bayesianNetworkTime0.setMomentParameters((MomentParameters)globalMomentsParam.getVectorTime0()); this.bayesianNetworkTimeT.setMomentParameters((MomentParameters)globalMomentsParam.getVectorTimeT()); vectorNatural.setVectorTime0(this.bayesianNetworkTime0.getNaturalParameters()); vectorNatural.setVectorTimeT(this.bayesianNetworkTimeT.getNaturalParameters()); this.naturalParameters=vectorNatural; }