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- Canopy_clustering_algorithm abstract "The canopy clustering algorithm is an unsupervised pre-clustering algorithm, often used as preprocessing step for the K-means algorithm or the Hierarchical clustering algorithm.It is intended to speed up clustering operations on large data sets, where using another algorithm directly may be impractical due to the size of the data set.The algorithm proceeds as follows: Cheaply partitioning the data into overlapping subsets (called "canopies") Perform more expensive clustering, but only within these canopiesSince the algorithm uses distance functions and requires the specification of distance thresholds, its applicability for high-dimensional data is limited by the curse of dimensionality. Only when a cheap and approximative – low-dimensional – distance function is available, the produced canopies will preserve the clusters produced by K-means.The method first appeared in a paper by Andrew McCallum, Kamal Nigam and Lyle Ungar.".
- Canopy_clustering_algorithm wikiPageID "14526742".
- Canopy_clustering_algorithm wikiPageRevisionID "604922982".
- Canopy_clustering_algorithm hasPhotoCollection Canopy_clustering_algorithm.
- Canopy_clustering_algorithm subject Category:Data_clustering_algorithms.
- Canopy_clustering_algorithm subject Category:Statistical_algorithms.
- Canopy_clustering_algorithm type Abstraction100002137.
- Canopy_clustering_algorithm type Act100030358.
- Canopy_clustering_algorithm type Activity100407535.
- Canopy_clustering_algorithm type Algorithm105847438.
- Canopy_clustering_algorithm type Cognition100023271.
- Canopy_clustering_algorithm type DataClusteringAlgorithms.
- Canopy_clustering_algorithm type Datum105816622.
- Canopy_clustering_algorithm type Event100029378.
- Canopy_clustering_algorithm type Information105816287.
- Canopy_clustering_algorithm type Procedure101023820.
- Canopy_clustering_algorithm type PsychologicalFeature100023100.
- Canopy_clustering_algorithm type Rule105846932.
- Canopy_clustering_algorithm type StatisticalAlgorithms.
- Canopy_clustering_algorithm type YagoPermanentlyLocatedEntity.
- Canopy_clustering_algorithm comment "The canopy clustering algorithm is an unsupervised pre-clustering algorithm, often used as preprocessing step for the K-means algorithm or the Hierarchical clustering algorithm.It is intended to speed up clustering operations on large data sets, where using another algorithm directly may be impractical due to the size of the data set.The algorithm proceeds as follows: Cheaply partitioning the data into overlapping subsets (called "canopies") Perform more expensive clustering, but only within these canopiesSince the algorithm uses distance functions and requires the specification of distance thresholds, its applicability for high-dimensional data is limited by the curse of dimensionality. ".
- Canopy_clustering_algorithm label "Canopy clustering algorithm".
- Canopy_clustering_algorithm sameAs m.03d6fbv.
- Canopy_clustering_algorithm sameAs Q5033439.
- Canopy_clustering_algorithm sameAs Q5033439.
- Canopy_clustering_algorithm sameAs Canopy_clustering_algorithm.
- Canopy_clustering_algorithm wasDerivedFrom Canopy_clustering_algorithm?oldid=604922982.
- Canopy_clustering_algorithm isPrimaryTopicOf Canopy_clustering_algorithm.