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#Net.sf.javaml.clustering Classes and Interfaces - 38 results found.
| Name | Description | Type | Package | Framework |
| AICScore | Class | net.sf.javaml.clustering.evaluation | JavaML | |
| AQBC | This class implements the Adaptive Quality-based Clustering Algorithm, based on the implementation in MATLAB by De Smet et al. | Class | net.sf.javaml.clustering | JavaML |
| BICScore | Class | net.sf.javaml.clustering.evaluation | JavaML | |
| CIndex | Class | net.sf.javaml.clustering.evaluation | JavaML | |
| Clusterer | A common interface for all clustering techniques. | Interface | net.sf.javaml.clustering | JavaML |
| ClusterEvaluation | This interface provides a frame for all measure that can be used to evaluate the quality of a clusterer. | Interface | net.sf.javaml.clustering.evaluation | JavaML |
| Cobweb | Class implementing the Cobweb and Classit clustering algorithms. | Class | net.sf.javaml.clustering | JavaML |
| DensityBasedSpatialClustering | Provides the density-based-spatial-scanning clustering algorithm. | Class | net.sf.javaml.clustering | JavaML |
| DoubleFormat | DoubleFormat formats double numbers into a specified digit format. | Class | net.sf.javaml.clustering.mcl | JavaML |
| ExpDouble | ExpDouble represents a double-precision number by a mantissa, a decimal exponent and the number of digits in the mantissa, in order to allow | Class | net.sf.javaml.clustering.mcl | JavaML |
| FarthestFirst | Cluster data using the FarthestFirst algorithm. | Class | net.sf.javaml.clustering | JavaML |
| Gamma | Class | net.sf.javaml.clustering.evaluation | JavaML | |
| GPlus | Class | net.sf.javaml.clustering.evaluation | JavaML | |
| HybridCentroidSimilarity | H_2 from the Zhao 2001 paperAuthor:Andreas De Rijcke | Class | net.sf.javaml.clustering.evaluation | JavaML |
| HybridPairwiseSimilarities | H_1 from the Zhao 2001 paperAuthor:Andreas De Rijcke | Class | net.sf.javaml.clustering.evaluation | JavaML |
| IterativeFarthestFirst | Class | net.sf.javaml.clustering | JavaML | |
| IterativeKMeans | This class implements an extension of KMeans. | Class | net.sf.javaml.clustering | JavaML |
| IterativeMultiKMeans | This class implements an extension of KMeans, combining Iterative- en MultiKMeans. | Class | net.sf.javaml.clustering | JavaML |
| KMeans | J. | Class | net.sf.javaml.clustering | JavaML |
| KMedoids | algorithm that is very much like k-means. | Class | net.sf.javaml.clustering | JavaML |
| MarkovClustering | MarkovClustering implements the Markov clustering (MCL) algorithm for graphs, using a HashMap-based sparse representation of a Markov matrix, i. | Class | net.sf.javaml.clustering.mcl | JavaML |
| MCL | Class | net.sf.javaml.clustering.mcl | JavaML | |
| MinMaxCut | G_1 from the Zhao 2001 paperAuthor:Andreas De Rijcke | Class | net.sf.javaml.clustering.evaluation | JavaML |
| MultiKMeans | This class implements an extension of KMeans (SKM). | Class | net.sf.javaml.clustering | JavaML |
| PointBiserial | Class | net.sf.javaml.clustering.evaluation | JavaML | |
| SOM | An implementation of the Self Organizing Maps algorithm as proposed by This implementation is derived from the Bachelor thesis of Tomi Suuronen | Class | net.sf.javaml.clustering | JavaML |
| SOM .GridType | Class | net.sf.javaml.clustering | JavaML | |
| SOM .LearningType | Class | net.sf.javaml.clustering | JavaML | |
| SOM .NeighbourhoodFunction | Class | net.sf.javaml.clustering | JavaML | |
| SparseMatrix | SparseMatrix is a sparse matrix with row-major format. | Class | net.sf.javaml.clustering.mcl | JavaML |
| SparseVector | SparseVector represents a sparse vector. | Class | net.sf.javaml.clustering.mcl | JavaML |
| SumOfAveragePairwiseSimilarities | I_1 from the Zhao 2001 paperAuthor:Andreas De Rijcke | Class | net.sf.javaml.clustering.evaluation | JavaML |
| SumOfCentroidSimilarities | TODO uitleg I_2 from Zhao 2001Author:Andreas De Rijcke | Class | net.sf.javaml.clustering.evaluation | JavaML |
| SumOfSquaredErrors | I_3 from the Zhao 2001 paperAuthor:Andreas De Rijcke | Class | net.sf.javaml.clustering.evaluation | JavaML |
| Tau | Class | net.sf.javaml.clustering.evaluation | JavaML | |
| TraceScatterMatrix | E_1 from the Zhao 2001 paper Distance measure has to be | Class | net.sf.javaml.clustering.evaluation | JavaML |
| Vectors | Static vector manipulation routines for Matlab porting and other numeric operations. | Class | net.sf.javaml.clustering.mcl | JavaML |
| WB | Class | net.sf.javaml.clustering.evaluation | JavaML | |