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| hashlookup:parent-total | 2 |
| hashlookup:trust | 60 |
The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:
| Key | Value |
|---|---|
| FileSize | 53864 |
| MD5 | EF56464B953650604EABF2FE9E5A2FA1 |
| PackageDescription | fast algorithms for single, average/UPGMA and complete linkage clustering; documentation This package provides a function to create a dendrogram from a list of items and a distance function between them. Initially a singleton cluster is created for each item, and then new, bigger clusters are created by merging the two clusters with least distance between them. The distance between two clusters is calculated according to the linkage type. The dendrogram represents not only the clusters but also the order on which they were created. . This package has many implementations with different performance characteristics. There are SLINK and CLINK algorithm implementations that are optimal in both space and time. There are also naive implementations using a distance matrix. Using the dendrogram function from Data.Clustering.Hierarchical automatically chooses the best implementation we have. . This package provides the documentation for a library for the Haskell programming language. See http://www.haskell.org/ for more information on Haskell. |
| PackageMaintainer | Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com> |
| PackageName | libghc-hierarchical-clustering-doc |
| PackageSection | doc |
| PackageVersion | 0.4.7-1build1 |
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| PackageDescription | fast algorithms for single, average/UPGMA and complete linkage clustering; documentation This package provides a function to create a dendrogram from a list of items and a distance function between them. Initially a singleton cluster is created for each item, and then new, bigger clusters are created by merging the two clusters with least distance between them. The distance between two clusters is calculated according to the linkage type. The dendrogram represents not only the clusters but also the order on which they were created. . This package has many implementations with different performance characteristics. There are SLINK and CLINK algorithm implementations that are optimal in both space and time. There are also naive implementations using a distance matrix. Using the dendrogram function from Data.Clustering.Hierarchical automatically chooses the best implementation we have. . This package provides the documentation for a library for the Haskell programming language. See http://www.haskell.org/ for more information on Haskell. |
| PackageMaintainer | Debian Haskell Group <pkg-haskell-maintainers@lists.alioth.debian.org> |
| PackageName | libghc-hierarchical-clustering-doc |
| PackageSection | doc |
| PackageVersion | 0.4.7-1 |
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