Apache
/
commons-math
mirror of https://github.com/apache/commons-math.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Fixed javadoc errors. 

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1462375 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Phil Steitz 2013-03-29 01:42:42 +00:00
parent 0b4e8b6bb0
commit b62b5b0306
2 changed files with 4 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

7
src/main/java/org/apache/commons/math3/distribution/fitting/MultivariateNormalMixtureExpectationMaximization.java
View File

@ -128,7 +128,6 @@ public class MultivariateNormalMixtureExpectationMaximization {
* or threshold is less than Double.MIN_VALUE * or threshold is less than Double.MIN_VALUE
* @throws DimensionMismatchException if initialMixture mean vector and data * @throws DimensionMismatchException if initialMixture mean vector and data
* number of columns are not equal * number of columns are not equal
* @see #estimateMultivariateNormalMixtureModelDistribution
*/ */
public void fit(final MixtureMultivariateNormalDistribution initialMixture, public void fit(final MixtureMultivariateNormalDistribution initialMixture,
final int maxIterations, final int maxIterations,
@ -275,7 +274,6 @@ public class MultivariateNormalMixtureExpectationMaximization {
* singular during fitting * singular during fitting
* @throws NotStrictlyPositiveException if numComponents is less than one or * @throws NotStrictlyPositiveException if numComponents is less than one or
* threshold is less than Double.MIN_VALUE * threshold is less than Double.MIN_VALUE
* @see #estimateMultivariateNormalMixtureModelDistribution
*/ */
public void fit(MixtureMultivariateNormalDistribution initialMixture) public void fit(MixtureMultivariateNormalDistribution initialMixture)
throws SingularMatrixException, throws SingularMatrixException,
@ -285,7 +283,7 @@ public class MultivariateNormalMixtureExpectationMaximization {
/** /**
* Helper method to create a multivariate normal mixture model which can be * Helper method to create a multivariate normal mixture model which can be
* used to initialize {@link #fit(MixtureMultivariateRealDistribution)}. * used to initialize {@link #fit(MixtureMultivariateNormalDistribution)}.
* *
* This method uses the data supplied to the constructor to try to determine * This method uses the data supplied to the constructor to try to determine
* a good mixture model at which to start the fit, but it is not guaranteed * a good mixture model at which to start the fit, but it is not guaranteed
@ -294,13 +292,12 @@ public class MultivariateNormalMixtureExpectationMaximization {
* @param data Data to estimate distribution * @param data Data to estimate distribution
* @param numComponents Number of components for estimated mixture * @param numComponents Number of components for estimated mixture
* @return Multivariate normal mixture model estimated from the data * @return Multivariate normal mixture model estimated from the data
* @throws NumberIsTooLargeException if {@code numComponents\ is greater * @throws NumberIsTooLargeException if {@code numComponents} is greater
* than the number of data rows. * than the number of data rows.
* @throws NumberIsTooSmallException if {@code numComponents < 2}. * @throws NumberIsTooSmallException if {@code numComponents < 2}.
* @throws NotStrictlyPositiveException if data has less than 2 rows * @throws NotStrictlyPositiveException if data has less than 2 rows
* @throws DimensionMismatchException if rows of data have different numbers * @throws DimensionMismatchException if rows of data have different numbers
* of columns * of columns
* @see #fit
*/ */
public static MixtureMultivariateNormalDistribution estimate(final double[][] data, public static MixtureMultivariateNormalDistribution estimate(final double[][] data,
final int numComponents) final int numComponents)

3
src/main/java/org/apache/commons/math3/ml/clustering/MultiKMeansPlusPlusClusterer.java
View File

@ -74,7 +74,8 @@ public class MultiKMeansPlusPlusClusterer<T extends Clusterable> extends Cluster
* @throws MathIllegalArgumentException if the data points are null or the number * @throws MathIllegalArgumentException if the data points are null or the number
* of clusters is larger than the number of data points * of clusters is larger than the number of data points
* @throws ConvergenceException if an empty cluster is encountered and the * @throws ConvergenceException if an empty cluster is encountered and the
* {@link #emptyStrategy} is set to {@code ERROR} * underlying {@link KMeansPlusPlusClusterer} has its
* {@link KMeansPlusPlusClusterer.EmptyClusterStrategy} is set to {@code ERROR}.
*/ */
public List<CentroidCluster<T>> cluster(final Collection<T> points) public List<CentroidCluster<T>> cluster(final Collection<T> points)
throws MathIllegalArgumentException, ConvergenceException { throws MathIllegalArgumentException, ConvergenceException {