|
||||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Objectedu.umass.cs.mallet.base.fst.Transducer
edu.umass.cs.mallet.base.fst.HMM
Hidden Markov Model
Nested Class Summary | |
static class |
HMM.State
|
protected static class |
HMM.TransitionIterator
|
Nested classes inherited from class edu.umass.cs.mallet.base.fst.Transducer |
Transducer.BeamLattice, Transducer.Lattice, Transducer.ViterbiLattice, Transducer.ViterbiPath, Transducer.ViterbiPath_NBest, Transducer.ViterbiPathBeam, Transducer.ViterbiPathBeamB, Transducer.ViterbiPathBeamFB, Transducer.ViterbiPathBeamKL |
Field Summary |
Fields inherited from class edu.umass.cs.mallet.base.fst.Transducer |
INFINITE_COST, inputPipe, outputPipe, ZERO_COST |
Constructor Summary | |
HMM(Alphabet inputAlphabet,
Alphabet outputAlphabet)
|
|
HMM(Pipe inputPipe,
Pipe outputPipe)
|
Method Summary | |
void |
addFullyConnectedStates(java.lang.String[] stateNames)
|
void |
addFullyConnectedStatesForBiLabels()
|
void |
addFullyConnectedStatesForLabels()
|
void |
addFullyConnectedStatesForThreeQuarterLabels(InstanceList trainingSet)
|
void |
addFullyConnectedStatesForTriLabels()
|
java.lang.String |
addOrderNStates(InstanceList trainingSet,
int[] orders,
boolean[] defaults,
java.lang.String start,
java.util.regex.Pattern forbidden,
java.util.regex.Pattern allowed,
boolean fullyConnected)
Assumes that the HMM's output alphabet contains String s. |
void |
addSelfTransitioningStateForAllLabels(java.lang.String name)
|
void |
addState(java.lang.String name,
double initialCost,
double finalCost,
java.lang.String[] destinationNames,
java.lang.String[] labelNames)
|
void |
addState(java.lang.String name,
java.lang.String[] destinationNames)
|
void |
addStatesForBiLabelsConnectedAsIn(InstanceList trainingSet)
Add states to create a second-order Markov model on labels, adding only those transitions the occur in the given trainingSet. |
void |
addStatesForHalfLabelsConnectedAsIn(InstanceList trainingSet)
Add as many states as there are labels, but don't create separate weights for each source-destination pair of states. |
void |
addStatesForLabelsConnectedAsIn(InstanceList trainingSet)
Add states to create a first-order Markov model on labels, adding only those transitions the occur in the given trainingSet. |
void |
addStatesForThreeQuarterLabelsConnectedAsIn(InstanceList trainingSet)
Add as many states as there are labels, but don't create separate observational-test-weights for each source-destination pair of states---instead have all the incoming transitions to a state share the same observational-feature-test weights. |
void |
estimate()
|
Alphabet |
getInputAlphabet()
|
Alphabet |
getOutputAlphabet()
|
Transducer.State |
getState(int index)
|
HMM.State |
getState(java.lang.String name)
|
java.util.Iterator |
initialStateIterator()
|
boolean |
isTrainable()
|
int |
numStates()
|
void |
print()
|
void |
reset()
|
boolean |
train(InstanceList ilist)
|
boolean |
train(InstanceList ilist,
InstanceList validation,
InstanceList testing)
|
boolean |
train(InstanceList ilist,
InstanceList validation,
InstanceList testing,
TransducerEvaluator eval)
|
void |
write(java.io.File f)
|
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
public HMM(Pipe inputPipe, Pipe outputPipe)
public HMM(Alphabet inputAlphabet, Alphabet outputAlphabet)
Method Detail |
public Alphabet getInputAlphabet()
public Alphabet getOutputAlphabet()
public void print()
print
in class Transducer
public void addState(java.lang.String name, double initialCost, double finalCost, java.lang.String[] destinationNames, java.lang.String[] labelNames)
public void addState(java.lang.String name, java.lang.String[] destinationNames)
public void addFullyConnectedStates(java.lang.String[] stateNames)
public void addFullyConnectedStatesForLabels()
public void addStatesForLabelsConnectedAsIn(InstanceList trainingSet)
public void addStatesForHalfLabelsConnectedAsIn(InstanceList trainingSet)
public void addStatesForThreeQuarterLabelsConnectedAsIn(InstanceList trainingSet)
public void addFullyConnectedStatesForThreeQuarterLabels(InstanceList trainingSet)
public void addFullyConnectedStatesForBiLabels()
public void addStatesForBiLabelsConnectedAsIn(InstanceList trainingSet)
public void addFullyConnectedStatesForTriLabels()
public void addSelfTransitioningStateForAllLabels(java.lang.String name)
public java.lang.String addOrderNStates(InstanceList trainingSet, int[] orders, boolean[] defaults, java.lang.String start, java.util.regex.Pattern forbidden, java.util.regex.Pattern allowed, boolean fullyConnected)
String
s. Creates an order-n HMM with input
predicates and output labels given by trainingSet
and order, connectivity, and weights given by the remaining
arguments.
trainingSet
- the training instancesorders
- an array of increasing non-negative numbers giving
the orders of the features for this HMM. The largest number
n is the Markov order of the HMM. States are
n-tuples of output labels. Each of the other numbers
k in orders
represents a weight set shared
by all destination states whose last (most recent) k
labels agree. If orders
is null
, an
order-0 HMM is built.defaults
- If non-null, it must be the same length as
orders
, with true
positions indicating
that the weight set for the corresponding order contains only the
weight for a default feature; otherwise, the weight set has
weights for all features built from input predicates.start
- The label that represents the context of the start of
a sequence. It may be also used for sequence labels.forbidden
- If non-null, specifies what pairs of successive
labels are not allowed, both for constructing norder
states or for transitions. A label pair (u,v)
is not allowed if u + "," + v matches
forbidden
.allowed
- If non-null, specifies what pairs of successive
labels are allowed, both for constructing norder
states or for transitions. A label pair (u,v)
is allowed only if u + "," + v matches
allowed
.fullyConnected
- Whether to include all allowed transitions,
even those not occurring in trainingSet
,public HMM.State getState(java.lang.String name)
public int numStates()
numStates
in class Transducer
public Transducer.State getState(int index)
getState
in class Transducer
public java.util.Iterator initialStateIterator()
initialStateIterator
in class Transducer
public boolean isTrainable()
isTrainable
in class Transducer
public void reset()
public void estimate()
public boolean train(InstanceList ilist)
train
in class Transducer
public boolean train(InstanceList ilist, InstanceList validation, InstanceList testing)
public boolean train(InstanceList ilist, InstanceList validation, InstanceList testing, TransducerEvaluator eval)
public void write(java.io.File f)
|
||||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |