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java.lang.Objectorg.encog.ml.hmm.distributions.ContinousDistribution
public class ContinousDistribution
A continuous distribution represents an infinite range of choices between two real numbers. A gaussian distribution is used to distribute the probability.
Constructor Summary | |
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ContinousDistribution(double[] mean,
double[][] covariance)
Construct a continuous distribution. |
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ContinousDistribution(int dimension)
Construct a continuous distribution with the specified number of dimensions. |
Method Summary | |
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ContinousDistribution |
clone()
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void |
fit(MLDataSet co)
Fit this distribution to the specified data set. |
void |
fit(MLDataSet co,
double[] weights)
Fit this distribution to the specified data set, given the specified weights, per element. |
MLDataPair |
generate()
Generate a random data pair, based on the probabilities. |
Matrix |
getCovariance()
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double[] |
getMean()
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double |
probability(MLDataPair o)
Determine the probability of the specified data pair. |
void |
update(double[][] covariance)
Update the covariance. |
Methods inherited from class java.lang.Object |
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equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public ContinousDistribution(double[] mean, double[][] covariance)
mean
- The mean.covariance
- The covariance.public ContinousDistribution(int dimension)
dimension
- The dimensions.Method Detail |
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public ContinousDistribution clone()
clone
in interface StateDistribution
clone
in class Object
public void fit(MLDataSet co)
fit
in interface StateDistribution
co
- The data set to fit to.public void fit(MLDataSet co, double[] weights)
fit
in interface StateDistribution
co
- The data set to fit to.weights
- The weights.public MLDataPair generate()
generate
in interface StateDistribution
public double probability(MLDataPair o)
probability
in interface StateDistribution
o
- The pair to consider.
public void update(double[][] covariance)
covariance
- The new covariance.public double[] getMean()
public Matrix getCovariance()
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