C++ (Cpp) MaximizationStep::addExpectations示例

示例#1

文件： emalg.cpp 项目： alucchi/structured_prediction_for_segmentation

Real EMAlg::iterate( MaximizationStep &mstep ) {
    Real logZ = 0;
    Real likelihood = 0;

    _estep.run();
    logZ = _estep.logZ();

    // Expectation calculation
    for( Evidence::const_iterator e = _evidence.begin(); e != _evidence.end(); ++e ) {
        InfAlg* clamped = _estep.clone();
        // Apply evidence
        for( Evidence::Observation::const_iterator i = e->begin(); i != e->end(); ++i )
            clamped->clamp( clamped->fg().findVar(i->first), i->second );
        clamped->init();
        clamped->run();

        likelihood += clamped->logZ() - logZ;

        mstep.addExpectations( *clamped );

        delete clamped;
    }

    // Maximization of parameters
    mstep.maximize( _estep.fg() );

    return likelihood;
}

示例#2

文件： UnsafeEmalg.cpp 项目： pyongjoo/enron

/** Only maximization step included
 *
 *  This function performs maximization based on the evidence collected from tab file
 *  Since there's no belief propagation stage, it does not return proper likelihood.
 */
Real UnsafeEmalg::iterateWithoutEstep(MaximizationStep &mstep) {
    Real logZ = 0;
    Real likelihood = 0;

    // Expectation calculation
    int nProcessed = 0;

    for( Evidence::const_iterator e = _evidence.begin(); e != _evidence.end(); ++e ) {
        InfAlg* clamped = _estep.clone();

        // Apply evidence
        for( Evidence::Observation::const_iterator i = e->begin(); i != e->end(); ++i )
            clamped->clamp( clamped->fg().findVar(i->first), i->second );

        mstep.addExpectations( *clamped );

        delete clamped;

        nProcessed++;

        if (nProcessed % 10 == 0) {
            cout << nProcessed << " number of samples processed" << endl;
        }
    }

    // Maximization of parameters
    mstep.maximize(_estep.fg());

    return likelihood;
}

示例#3

文件： dai_map.cpp 项目： benihana/HadoopBNEM

Real EM_estep(MaximizationStep &mstep, const Evidence &evidence, InfAlg &inf) {
	Real likelihood = 0;

	inf.run();
	Real logZ = inf.logZ();

	// Expectation calculation
	for (Evidence::const_iterator e = evidence.begin(); e != evidence.end(); ++e) {
		InfAlg* clamped = inf.clone();
		// Apply evidence
		for (Evidence::Observation::const_iterator i = e->begin(); i != e->end(); ++i)
			clamped->clamp(clamped->fg().findVar(i->first), i->second);
		clamped->init();
		clamped->run();

		likelihood += clamped->logZ() - logZ;

		mstep.addExpectations(*clamped);

		delete clamped;
	}

	return likelihood;
}