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;
}
/** 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;
}