canStopEM() | PLearn::RandomVariable | [virtual] |
classname() | PLearn::MultinomialRandomVariable | [inline, virtual] |
clearEMmarks() | PLearn::RandomVariable | [virtual] |
ElogP(const Var &obs, RVArray ¶meters_to_learn, const RVInstanceArray &RHS) | PLearn::RandomVariable | [virtual] |
EM(const RVArray ¶meters_to_learn, VarArray &prop_path, VarArray &observedVars, VMat distr, int n_samples, int max_n_iterations, real relative_improvement_threshold, bool accept_worsening_likelihood=false) | PLearn::RandomVariable | [virtual] |
EMBprop(const Vec obs, real posterior) | PLearn::MultinomialRandomVariable | [virtual] |
EMEpochInitialize() | PLearn::MultinomialRandomVariable | [virtual] |
EMmark | PLearn::RandomVariable | [protected] |
EMTrainingInitialize(const RVArray ¶meters_to_learn) | PLearn::RandomVariable | [virtual] |
EMUpdate() | PLearn::MultinomialRandomVariable | [virtual] |
epoch(VarArray &prop_path, VarArray &observed_vars, const VMat &distr, int n_samples, bool do_EM_learning=true) | PLearn::RandomVariable | [virtual] |
isColumnVec() | PLearn::RandomVariable | [inline] |
isConstant() | PLearn::RandomVariable | [inline] |
isDiscrete() | PLearn::MultinomialRandomVariable | [virtual] |
isMarked() | PLearn::RandomVariable | [inline, virtual] |
isNonRandom() | PLearn::StochasticRandomVariable | [inline, virtual] |
isRowVec() | PLearn::RandomVariable | [inline] |
isScalar() | PLearn::RandomVariable | [inline] |
isVec() | PLearn::RandomVariable | [inline] |
learn_the_parameters | PLearn::RandomVariable | [protected] |
learn_the_probabilities() | PLearn::MultinomialRandomVariable | [inline] |
length() | PLearn::RandomVariable | [inline, virtual] |
log_probabilities() | PLearn::MultinomialRandomVariable | [inline] |
logP(const Var &obs, const RVInstanceArray &RHS, RVInstanceArray *parameters_to_learn) | PLearn::MultinomialRandomVariable | [virtual] |
mark(Var v) | PLearn::RandomVariable | [inline, virtual] |
mark() | PLearn::RandomVariable | [inline, virtual] |
marked | PLearn::RandomVariable | [protected] |
markRHSandSetKnownValues(const RVInstanceArray &RHS) | PLearn::RandomVariable | [inline] |
MultinomialRandomVariable(const RandomVar &log_probabilities) | PLearn::MultinomialRandomVariable | |
nelems() | PLearn::RandomVariable | [inline] |
P(const Var &obs, const RVInstanceArray &RHS) | PLearn::RandomVariable | [virtual] |
parents | PLearn::RandomVariable | |
pmark | PLearn::RandomVariable | [protected] |
PPointable() | PLearn::PPointable | [inline] |
PPointable(const PPointable &other) | PLearn::PPointable | [inline] |
RandomVariable(int thelength, int thewidth=1) | PLearn::RandomVariable | |
RandomVariable(const Vec &the_value) | PLearn::RandomVariable | |
RandomVariable(const Mat &the_value) | PLearn::RandomVariable | |
RandomVariable(const Var &the_value) | PLearn::RandomVariable | |
RandomVariable(const RVArray &parents, int thelength) | PLearn::RandomVariable | |
RandomVariable(const RVArray &parents, int thelength, int thewidth) | PLearn::RandomVariable | |
ref() const | PLearn::PPointable | [inline] |
rv_number | PLearn::RandomVariable | [protected] |
setKnownValues() | PLearn::StochasticRandomVariable | [virtual] |
setValueFromParentsValue() | PLearn::MultinomialRandomVariable | [virtual] |
StochasticRandomVariable(int length=1) | PLearn::StochasticRandomVariable | |
StochasticRandomVariable(const RVArray ¶ms, int length) | PLearn::StochasticRandomVariable | |
StochasticRandomVariable(const RVArray ¶ms, int length, int width) | PLearn::StochasticRandomVariable | |
subVec(int start, int length) | PLearn::RandomVariable | |
sum_posteriors | PLearn::MultinomialRandomVariable | [protected] |
unmark() | PLearn::RandomVariable | [inline, virtual] |
unmarkAncestors() | PLearn::RandomVariable | [virtual] |
unref() const | PLearn::PPointable | [inline] |
usage() const | PLearn::PPointable | [inline] |
value | PLearn::RandomVariable | |
width() | PLearn::RandomVariable | [inline, virtual] |
~PPointable() | PLearn::PPointable | [inline, virtual] |
~RandomVariable() | PLearn::RandomVariable | [virtual] |