public static class BinomialDistribution.MaximumLikelihoodEstimator extends AbstractCloneableSerializable implements DistributionEstimator<java.lang.Number,BinomialDistribution>
| Constructor and Description |
|---|
MaximumLikelihoodEstimator()
Default constructor
|
| Modifier and Type | Method and Description |
|---|---|
BinomialDistribution.PMF |
learn(java.util.Collection<? extends java.lang.Number> data)
The
learn method creates an object of ResultType using
data of type DataType, using some form of "learning" algorithm. |
cloneequals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitclonepublic MaximumLikelihoodEstimator()
public BinomialDistribution.PMF learn(java.util.Collection<? extends java.lang.Number> data)
BatchLearnerlearn method creates an object of ResultType using
data of type DataType, using some form of "learning" algorithm.learn in interface BatchLearner<java.util.Collection<? extends java.lang.Number>,BinomialDistribution>data - The data that the learning algorithm will use to create an
object of ResultType.