►CCluE::Algorithm | Abstract base class for algorithms |
CCluE::AdaptiveSampling< T > | K-means++ sampling method |
CCluE::Agglomerative< T > | Agglomerative clustering algorithm |
CCluE::BalcanBlumGupta< T > | BalcanBlumGupta algorithm |
CCluE::BruteForceClustering< T > | Brute force k-median / k-means clustering |
CCluE::DasguptaLong< T > | DasguptaLong algorithm |
CCluE::FarthestFirstTraversal< T > | Farthest first traversal algorithm |
CCluE::Gonzales< T > | Gonzales algorithm |
CCluE::KumarSabharwalSen< T > | KumarSabharwalSen algorithm |
CCluE::Lloydtype< T > | Lloyd type algorithm |
CCluE::LloydtypeCF< T > | Lloyd type algorithm using clustering features |
CCluE::ProxyBasedAgglo< T > | Agglomerative proxy-based clustering algorithm |
►CCluE::StreamingAlgorithm< T > | Abstract base class for streaming algorithms |
CCluE::Birch< T > | BIRCH clustering algorithm |
CCluE::UniformSampling< T > | Uniform sampling |
►CCluE::StreamingAlgorithm< VectorType > | |
CCluE::FrahlingSohler< VectorType, Hash, size_space > | Coreset algorithm for k-median clustering |
CCluE::AttributeCalculator< T > | Abstract base class for attribute calculation (e.g. diameter) |
►CCluE::AttributeCalculator< CFEntry< T > > | |
CCluE::CFDiameter< T > | Calculates the diameter D of a given CFEntry |
CCluE::AttributeCalculator< CluE::CFEntry< T > > | |
CCluE::BirchConfig< T > | BIRCH configuration class |
►CCluE::CFEntry< T > | Clustering feature tree entry |
CCluE::CFREntry< T > | Clustering feature with representation point |
CCluE::CFTree< T > | Clustering feature tree |
►CCluE::CluEException | CluE related exceptions base class |
CCluE::InvalidArgumentException | Indicates invalid values of arguments |
CCluE::InvalidRuntimeConfigurationException | Indicates that a computation entered an invalid configuration state |
►CCluE::ClusterDissimilarityMeasure< T > | Abstract base class for cluster dissimilarity measurement |
CCluE::AverageLinkage< T > | Average cluster linkage |
CCluE::CompleteLinkage< T > | Complete cluster linkage |
CCluE::SingleLinkage< T > | Single cluster linkage |
►CCluE::ClusterMeasureSetter< T > | Interface to propagate the ability to set a ClusterDissimilarityMeasure |
CCluE::Agglomerative< T > | Agglomerative clustering algorithm |
CCluE::DiscreteBoundedSpace< VectorType, size_space > | Interface to extend a template type to provide discrete (bounded) space {0, ..., n-1}^d features |
►CCluE::DiscreteBoundedSpace< Point, unsigned long long > | |
CCluE::DiscreteBoundedRealSpaceProvider | Provides discrete bounded space features for Point |
►CCluE::DiscreteProxyProvider< T > | Abstract base class to access the results of proxy / center based clustering algorithms |
CCluE::DiscreteDoubleSolution< T > | Data structure for partitions and discrete proxies |
CCluE::DiscreteProxySolution< T > | Data structure for discrete proxies |
CCluE::DissimilarityMeasure< T > | Abstract base class for dissimilarity measurement |
►CCluE::DissimilarityMeasure< CFEntry< T > > | |
CCluE::CFAverageInterClusterDistance< T > | Calculates the average inter-cluster distance D2 of a given CFEntry |
CCluE::DissimilarityMeasure< CluE::CFEntry< T > > | |
►CCluE::DissimilarityMeasure< FrequencyDistribution > | |
CCluE::FrequencyKLD | Kullback-leibler divergence for FrequencyDistribution |
►CCluE::DissimilarityMeasure< Point > | |
CCluE::L1Metric | L1 metric for Point |
CCluE::L2Metric | L2 metric for Point |
CCluE::LPMetric | Lp metric for Point |
CCluE::PointKLD | Kullback-Leibler divergence for Point |
CCluE::SquaredL1Metric | Squared L1 metric for Point |
CCluE::SquaredL2Metric | Squared L2 metric for Point |
CCluE::SquaredLPMetric | Squared Lp metric for Point |
CCluE::DistinctElements< U, H > | Count distinct elements in a data stream |
CCluE::DistinctElementsPrimitive< U, H > | Count distinct elements in a stream using a std::set (for debugging) |
CCluE::DistinctElementsPrimitive< unsigned long long, unsigned long long > | |
CCluE::Distribution< T > | Abstract base class for probability distributions |
►CCluE::Distribution< double > | |
CCluE::UniGauss | Univariate normal distribution |
►CCluE::Distribution< Point > | |
CCluE::PointGauss | Univariate normal distribution |
CCluE::PointGMM | Gaussian Mixture Model distribution |
CCluE::DynamicBitset< T > | Dynamic bitset similiar to boost::dynamic_bitset |
CCluE::EuclideanSpaceProvider< VectorType > | Interface to extend a template type to provide euclidean vector space features |
►CCluE::EuclideanSpaceProvider< Point > | |
CCluE::RealSpaceProvider | Provides euclidean vector space features for Point |
CCluE::EuclideanSpaceProvider< T > | |
►CCluE::Evaluation | Abstract base class for clustering evaluations |
►CCluE::CombinedEvaluation< T > | Abstract class. Proxy based evaluation algorithms may be optimized by deriving from this class |
CCluE::KCenterEvaluator< T > | Calculates the k-center weight |
CCluE::KMeansEvaluator< T > | Calculates the k-means weight |
►CCluE::PartitionEvaluation< T > | Abstract class for partition-based evaluation algorithms |
CCluE::CombinedToPartitionEvaluationWrapper< T > | Wraps CombinedEvaluation into PartitionEvaluation by using a ProxGenerator instance |
CCluE::MaxDiamEvaluator< T > | Calculates the maximum diameter of one or more given clusters |
►CCluE::ProxyEvaluation< T > | Abstract class for proxy-based evaluation algorithms |
CCluE::KCenterEvaluator< T > | Calculates the k-center weight |
CCluE::KMeansEvaluator< T > | Calculates the k-means weight |
CCluE::FrequencyDistribution | Probability distribution on non-negative integers |
CCluE::GraycodeSequence | Returns the bits flipped in a Graycode sequence |
CCluE::FrahlingSohler< VectorType, Hash, size_space >::GridInstance::Grid | A single grid |
CCluE::FrahlingSohler< VectorType, Hash, size_space >::GridInstance | Set of grids |
►CCluE::HashFunction< U, H > | Base class template for any hash function mapping an element from universe U to hashing space H |
CCluE::CarterWegman< U, H > | Universal hashing |
►CCluE::HashFunction< unsigned long long, size_t > | |
CCluE::CarterWegman< unsigned long long, size_t > | |
►CCluE::HashFunction< unsigned long long, unsigned long long > | |
CCluE::CarterWegman< unsigned long long, unsigned long long > | |
►CCluE::InputSetter< T > | Interface to propagate the ability to set input data |
CCluE::AdaptiveSampling< T > | K-means++ sampling method |
CCluE::Agglomerative< T > | Agglomerative clustering algorithm |
CCluE::BalcanBlumGupta< T > | BalcanBlumGupta algorithm |
CCluE::BruteForceClustering< T > | Brute force k-median / k-means clustering |
CCluE::DasguptaLong< T > | DasguptaLong algorithm |
CCluE::FarthestFirstTraversal< T > | Farthest first traversal algorithm |
CCluE::Gonzales< T > | Gonzales algorithm |
CCluE::KumarSabharwalSen< T > | KumarSabharwalSen algorithm |
CCluE::Lloydtype< T > | Lloyd type algorithm |
CCluE::LloydtypeCF< T > | Lloyd type algorithm using clustering features |
CCluE::ProxyBasedAgglo< T > | Agglomerative proxy-based clustering algorithm |
CCluE::UniformSampling< T > | Uniform sampling |
CCluE::Matrix | Weighted matrix of arbitrary dimension |
►CCluE::MeasureSetter< T > | Interface to propagate the ability to set a DissimilarityMeasure |
CCluE::AdaptiveSampling< T > | K-means++ sampling method |
CCluE::BalcanBlumGupta< T > | BalcanBlumGupta algorithm |
CCluE::BruteForceClustering< T > | Brute force k-median / k-means clustering |
CCluE::DasguptaLong< T > | DasguptaLong algorithm |
CCluE::FarthestFirstTraversal< T > | Farthest first traversal algorithm |
CCluE::Gonzales< T > | Gonzales algorithm |
CCluE::KCenterEvaluator< T > | Calculates the k-center weight |
CCluE::KMeansEvaluator< T > | Calculates the k-means weight |
CCluE::KumarSabharwalSen< T > | KumarSabharwalSen algorithm |
CCluE::Lloydtype< T > | Lloyd type algorithm |
CCluE::LloydtypeCF< T > | Lloyd type algorithm using clustering features |
CCluE::MaxDiamEvaluator< T > | Calculates the maximum diameter of one or more given clusters |
CCluE::ProxyBasedAgglo< T > | Agglomerative proxy-based clustering algorithm |
►CCluE::PartitionProvider< T > | Abstract base class to access results of partition based clustering algorithms |
CCluE::DiscreteDoubleSolution< T > | Data structure for partitions and discrete proxies |
►CCluE::DoubleSolution< T > | Data structure for partitions and proxies |
CCluE::LloydtypeCFSolution< T > | LloydtypeCF specific DoubleSolution |
CCluE::PartitionSolution< T > | Data structure for partitions |
CCluE::PointSetDistance< T > | Calculates the (minimum) distance between a point and a set of points |
CCluE::PrimeGenerator | Generates numbers which are (most likely) prime numbers |
CCluE::ProxyGenerator< T > | Abstract base class for mechanisms that compute a proxy or representative object for a given set of objects, e.g. a cluster center |
►CCluE::ProxyGenerator< FrequencyDistribution > | |
CCluE::FrequencyCentroid | Weighted centroid for FrequencyDistribution |
►CCluE::ProxyGenerator< Point > | |
CCluE::PointCentroid | Center of gravity for Point |
►CCluE::ProxyProvider< T > | Abstract base class to access results of proxy / center based clustering algorithms |
CCluE::DoubleSolution< T > | Data structure for partitions and proxies |
CCluE::ProxySolution< T > | Data structure for proxies |
CRandomGenerator | Encapsulates an STL random generator |
CCluE::Randomness | Random number generator |
►CCluE::SetIterator< T > | Base class used to provide iterating over sets |
CCluE::FixedSizeSubsetIterator< T > | Iterates over all fixed-size subsets of a given superset |
CCluE::SubsetIterator< T > | Iterates over all subsets of a given superset |
►CCluE::SolutionProvider | Abstract base class for algorithm solutions |
CCluE::DiscreteDoubleSolution< T > | Data structure for partitions and discrete proxies |
CCluE::DiscreteProxySolution< T > | Data structure for discrete proxies |
CCluE::DoubleSolution< T > | Data structure for partitions and proxies |
CCluE::PartitionSolution< T > | Data structure for partitions |
CCluE::ProxySolution< T > | Data structure for proxies |
CCluE::KumarSabharwalSen< T >::Tupel | Used to return a DoubleSolution and its cost |
►Cunary_function | |
►CCluE::CFTree< T >::ThresholdCalculator | Threshold calculation functor class |
CCluE::Birch< T >::ThreshFuncRedirector | Wraps around a BirchConfig object to provide threshold calculation |
►CCluE::WeightedObject | Abstract base class for weighted objects |
CCluE::Point | Weighted point of arbitrary dimension |
CCluE::WeightModifier< T > | Abstract base class to modify the weight of weighted objects |
►CCluE::WeightModifier< Point > | |
CCluE::PointWeightModifier | Modifies the weight of a Point |