org.encog.ml.hmm
public class HiddenMarkovModel extends BasicML implements MLStateSequence, Serializable, Cloneable
Modifier and Type | Field and Description |
---|---|
static String |
TAG_COVARIANCE |
static String |
TAG_DIST_TYPE |
static String |
TAG_ITEMS |
static String |
TAG_MEAN |
static String |
TAG_PI |
static String |
TAG_PROBABILITIES |
static String |
TAG_STATES |
static String |
TAG_TRANSITION |
Constructor and Description |
---|
HiddenMarkovModel(int states)
Construct a discrete HMM with the specified number of states.
|
HiddenMarkovModel(int theStates,
int theItems) |
HiddenMarkovModel(int theStates,
int[] theItems) |
Modifier and Type | Method and Description |
---|---|
HiddenMarkovModel |
clone() |
HiddenMarkovModel |
cloneStructure() |
StateDistribution |
createNewDistribution() |
int[] |
getItems() |
double[] |
getPi() |
double |
getPi(int i) |
int |
getStateCount() |
StateDistribution |
getStateDistribution(int i) |
int[] |
getStatesForSequence(MLDataSet seq)
Get the sates for the given sequence.
|
double[][] |
getTransitionProbability() |
double |
getTransitionProbability(int i,
int j) |
boolean |
isContinuous() |
boolean |
isDiscrete() |
double |
lnProbability(MLDataSet seq) |
double |
probability(MLDataSet seq)
Determine the probability of the specified sequence.
|
double |
probability(MLDataSet seq,
int[] states)
Determine the probability for the specified sequence and states.
|
void |
setPi(double[] data) |
void |
setPi(int i,
double value) |
void |
setStateDistribution(int i,
StateDistribution dist) |
void |
setTransitionProbability(double[][] data) |
void |
setTransitionProbability(int i,
int j,
double value) |
void |
updateProperties()
Update any objeccts when a property changes.
|
getProperties, getPropertyDouble, getPropertyLong, getPropertyString, setProperty, setProperty, setProperty
public static final String TAG_STATES
public static final String TAG_ITEMS
public static final String TAG_PI
public static final String TAG_TRANSITION
public static final String TAG_DIST_TYPE
public static final String TAG_MEAN
public static final String TAG_COVARIANCE
public static final String TAG_PROBABILITIES
public HiddenMarkovModel(int states)
states
- The number of states.public HiddenMarkovModel(int theStates, int theItems)
public HiddenMarkovModel(int theStates, int[] theItems)
public HiddenMarkovModel clone() throws CloneNotSupportedException
clone
in class Object
CloneNotSupportedException
public HiddenMarkovModel cloneStructure()
public StateDistribution createNewDistribution()
public double getPi(int i)
public int getStateCount()
public StateDistribution getStateDistribution(int i)
public int[] getStatesForSequence(MLDataSet seq)
MLStateSequence
getStatesForSequence
in interface MLStateSequence
seq
- The sequence.public double getTransitionProbability(int i, int j)
public boolean isContinuous()
public boolean isDiscrete()
public double lnProbability(MLDataSet seq)
public double probability(MLDataSet seq)
MLStateSequence
probability
in interface MLStateSequence
seq
- The sequence.public double probability(MLDataSet seq, int[] states)
MLStateSequence
probability
in interface MLStateSequence
seq
- The sequence.states
- The states.public void setPi(int i, double value)
public void setStateDistribution(int i, StateDistribution dist)
public void setTransitionProbability(int i, int j, double value)
public void updateProperties()
MLProperties
updateProperties
in interface MLProperties
updateProperties
in class BasicML
public int[] getItems()
public double[] getPi()
public double[][] getTransitionProbability()
public void setTransitionProbability(double[][] data)
public void setPi(double[] data)
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