@Override public void setRandom(Random random) { ArgumentChecker.assertIsNotNull("random", random); this.random = random; }
@Override public void setRandom(Random random) { ArgumentChecker.assertIsNotNull("random", random); this.random = random; }
/** * Sets the cluster creator used to create the initial clusters. * * @param creator * The new cluster creator. */ public void setCreator( ClusterCreator<ClusterType, DataType> creator) { ArgumentChecker.assertIsNotNull("creator", creator); this.creator = creator; }
/** * Sets the cluster creator used to create the initial clusters. * * @param creator * The new cluster creator. */ public void setCreator( ClusterCreator<ClusterType, DataType> creator) { ArgumentChecker.assertIsNotNull("creator", creator); this.creator = creator; }
/** * Sets the cluster creator used to create the initial clusters. * * @param creator * The new cluster creator. */ public void setCreator( ClusterCreator<ClusterType, DataType> creator) { ArgumentChecker.assertIsNotNull("creator", creator); this.creator = creator; }
/** * Sets the cluster creator. * * @param creator The creator for clusters. */ public void setCreator( IncrementalClusterCreator<ClusterType, DataType> creator) { ArgumentChecker.assertIsNotNull("creator", creator); this.creator = creator; }
/** * Sets the cluster creator. * * @param creator The creator for clusters. */ public void setCreator( IncrementalClusterCreator<ClusterType, DataType> creator) { ArgumentChecker.assertIsNotNull("creator", creator); this.creator = creator; }
/** * Sets the cluster creator. * * @param creator The creator for clusters. */ public void setCreator( IncrementalClusterCreator<ClusterType, DataType> creator) { ArgumentChecker.assertIsNotNull("creator", creator); this.creator = creator; }
@Override public void setRandom(Random random) { ArgumentChecker.assertIsNotNull("random", random); this.random = random; }
/** * Sets the metric on clusters used for partitioning. * * @param clusterDivergenceFunction The metric on clusters */ public void setWithinClusterDivergenceFunction( WithinClusterDivergence<? super ClusterType, ? super DataType> clusterDivergenceFunction) { ArgumentChecker.assertIsNotNull("clusterDivergenceFunction", clusterDivergenceFunction); this.clusterDivergenceFunction = clusterDivergenceFunction; this.divergenceFunction = null; }
/** * Sets the metric on clusters used for partitioning. * * @param clusterDivergenceFunction The metric on clusters */ public void setWithinClusterDivergenceFunction( WithinClusterDivergence<? super ClusterType, ? super DataType> clusterDivergenceFunction) { ArgumentChecker.assertIsNotNull("clusterDivergenceFunction", clusterDivergenceFunction); this.clusterDivergenceFunction = clusterDivergenceFunction; this.divergenceFunction = null; }
/** * Sets the metric on clusters used for partitioning. * * @param clusterDivergenceFunction The metric on clusters */ public void setWithinClusterDivergenceFunction( WithinClusterDivergence<? super ClusterType, ? super DataType> clusterDivergenceFunction) { ArgumentChecker.assertIsNotNull("clusterDivergenceFunction", clusterDivergenceFunction); this.clusterDivergenceFunction = clusterDivergenceFunction; this.divergenceFunction = null; }
/** * Adds a given member to the ensemble. * * @param member * The ensemble member to add. */ public void add( final MemberType member) { ArgumentChecker.assertIsNotNull("member", member); this.getMembers().add(member); }
/** * Adds a given member to the ensemble. * * @param member * The ensemble member to add. */ public void add( final MemberType member) { ArgumentChecker.assertIsNotNull("member", member); this.getMembers().add(member); }
/** * Adds a given member to the ensemble. * * @param member * The ensemble member to add. */ public void add( final MemberType member) { ArgumentChecker.assertIsNotNull("member", member); this.getMembers().add(member); }
/** * Adds a given member to the ensemble. * * @param member * The ensemble member to add. */ public void add( final MemberType member) { ArgumentChecker.assertIsNotNull("member", member); this.getMembers().add(member); }
/** * Adds a given member to the ensemble. * * @param member * The ensemble member to add. */ public void add( final MemberType member) { ArgumentChecker.assertIsNotNull("member", member); this.getMembers().add(member); }
/** * Adds a given member to the ensemble. * * @param member * The ensemble member to add. */ public void add( final MemberType member) { ArgumentChecker.assertIsNotNull("member", member); this.getMembers().add(member); }
/** * Adds the given categorizer with a given weight. * * @param member The categorizer to add. * @param weight The weight for the new member. */ public void add( final MemberType member, final double weight) { ArgumentChecker.assertIsNotNull("member", member); final WeightedValue<MemberType> weighted = DefaultWeightedValue.create(member, weight); this.getMembers().add(weighted); }
/** * Use a metric between a cluster and a point to update the metric on * clusters. * * @param divergenceFunction The metric between a point and a point used to * update the metric on clusters. */ public void setDivergenceFunction( DivergenceFunction<? super ClusterType, ? super DataType> divergenceFunction) { ArgumentChecker.assertIsNotNull("divergenceFunction", divergenceFunction); this.setWithinClusterDivergenceFunction( new WithinClusterDivergenceWrapper<>(divergenceFunction)); this.divergenceFunction = divergenceFunction; }