Parents (Total: 21)

The searched file hash is included in 21 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	117808
MD5	36E3EBCB4F2330194784FA9F3C0550D2
PackageDescription	fast algorithms for single, average/UPGMA and complete linkage clustering 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 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-dev
PackageSection	haskell
PackageVersion	0.4.6-5+b2
SHA-1	0372965B506BAD261EB012225EC6135A2E66F875
SHA-256	30C73E224960475E3D8175F02514E6351BC7CD02945A0AFA6A53842C8F880B9B

Key	Value
FileSize	78236
MD5	8665881786B9BDA4438B8C4D838B6435
PackageDescription	fast algorithms for single, average/UPGMA and complete linkage clustering; profiling libraries 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 a library for the Haskell programming language, compiled for profiling. 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-prof
PackageSection	haskell
PackageVersion	0.4.6-5+b2
SHA-1	22817DE7CD40FEA5FCE31BC19CA4F110F094175A
SHA-256	69733F7B069BCD7FD2CF7C05A75AF5942FF11AD13E42554F305EFF0FDADC606A

Key	Value
FileSize	80532
MD5	0C9A9967E7B2859D91BBDD8B8051D13E
PackageDescription	fast algorithms for single, average/UPGMA and complete linkage clustering; profiling libraries 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 a library for the Haskell programming language, compiled for profiling. 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-prof
PackageSection	haskell
PackageVersion	0.4.6-5+b3
SHA-1	2851F63B4D5BFD951F30A9EF6C59E56050A61043
SHA-256	A41236692D7D25E7CC7D4CCAE3F017148C29526EFAA627B10D3A754953D75B05

Key	Value
FileSize	93708
MD5	AD84127EC3642A9BD946B89D16BF14F5
PackageDescription	fast algorithms for single, average/UPGMA and complete linkage clustering 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 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-dev
PackageSection	haskell
PackageVersion	0.4.6-5+b2
SHA-1	3369781F3A751B18AA95CF3F7A5B3001DBFCA60F
SHA-256	DFF0793055CCF67DC2B1419D5D9B4BE6CB6A359718A4A21830D47505560CB008

Key	Value
FileSize	92668
MD5	51EDB44A1F543A2795DBDC4DAF6CA72B
PackageDescription	fast algorithms for single, average/UPGMA and complete linkage clustering; profiling libraries 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 a library for the Haskell programming language, compiled for profiling. 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-prof
PackageSection	haskell
PackageVersion	0.4.6-5+b2
SHA-1	34CE598D978A908CF9CDC9007C88BD8043DE9489
SHA-256	43820EFAB6857B6BCD7267518D277D9E2BBF3424C8DA33C9BCB33A7304ACCFB1

Key	Value
FileSize	88644
MD5	2C5FDE3EEF4982A313720B32C0D23BE5
PackageDescription	fast algorithms for single, average/UPGMA and complete linkage clustering; profiling libraries 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 a library for the Haskell programming language, compiled for profiling. 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-prof
PackageSection	haskell
PackageVersion	0.4.6-5+b2
SHA-1	403D7B850A556A53F4B927D84C84889EF87C6583
SHA-256	0488FF958394AE2A575D6BF320296CCF6490B362BDFBAD5C3038178F06980839

Key	Value
FileSize	105824
MD5	7FF7C630FC5B6505C8C2282BF2624718
PackageDescription	fast algorithms for single, average/UPGMA and complete linkage clustering 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 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-dev
PackageSection	haskell
PackageVersion	0.4.6-5+b2
SHA-1	5452CCE012B012CA807B521CD3F3DE1065D42074
SHA-256	03AB3EE0583CAB9E99A350E59548F6B4979A8826C76ED59512985AF5990EBE2F

Key	Value
FileSize	93160
MD5	C1D1F13F4552502C6D286E161E7FDAD6
PackageDescription	fast algorithms for single, average/UPGMA and complete linkage clustering; profiling libraries 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 a library for the Haskell programming language, compiled for profiling. 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-prof
PackageSection	haskell
PackageVersion	0.4.6-5+b2
SHA-1	58FD8BE7C905DB7D682E943C82DA4B10A8737887
SHA-256	E3685916BF14D858FD120C152681417157CF57603CEA473E9F34BC06B7B11815

Key	Value
FileSize	112376
MD5	AAF28A350A10B8D5F57148BA74E65B28
PackageDescription	fast algorithms for single, average/UPGMA and complete linkage clustering 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 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-dev
PackageSection	haskell
PackageVersion	0.4.6-5+b2
SHA-1	711D90531E38ECE86C7CA3325EFABD1665ACC5A3
SHA-256	8D4BE9E37D2BDC7C567FB6B75F5AFEA2F6CE3227BA2C038385E89234090D70C2

Key	Value
FileSize	94700
MD5	9FFB830BE1757DBEC9B41391372B7450
PackageDescription	fast algorithms for single, average/UPGMA and complete linkage clustering; profiling libraries 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 a library for the Haskell programming language, compiled for profiling. 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-prof
PackageSection	haskell
PackageVersion	0.4.6-5+b2
SHA-1	8308F769C1F5414D0A76C01198155E7F78115B45
SHA-256	AE9DE43D03C106A8F16196640B1058C87ACBECA0F9DB4587DF50CBB44C1D1B23