name: rp-tree version: 0.3.5 x-revision: 1 synopsis: Random projection trees description: Random projection trees for approximate nearest neighbor search in high-dimensional vector spaces . To use the library, import "Data.RPTree", which also contains all documentation. homepage: https://github.com/ocramz/rp-tree license: BSD3 license-file: LICENSE author: Marco Zocca maintainer: ocramz copyright: 2021 Marco Zocca category: Data Mining, Data Structures, Machine Learning, Data build-type: Simple extra-source-files: README.md Changelog.md extra-doc-files: r/scatter.png cabal-version: 1.18 tested-with: GHC == 8.10.4 library default-language: Haskell2010 ghc-options: -Wall hs-source-dirs: src exposed-modules: Data.RPTree other-modules: Data.RPTree.Internal Data.RPTree.Gen Data.RPTree.Draw Data.RPTree.Conduit Data.RPTree.Internal.Testing build-depends: base >= 4.7 && < 5 , boxes , bytestring , conduit , containers , deepseq , serialise , splitmix , splitmix-distributions , transformers , vector , vector-algorithms test-suite spec default-language: Haskell2010 ghc-options: -Wall type: exitcode-stdio-1.0 hs-source-dirs: test main-is: Spec.hs build-depends: base , rp-tree , conduit , hspec , QuickCheck , splitmix-distributions benchmark bench-time default-language: Haskell2010 ghc-options: -threaded -O2 type: exitcode-stdio-1.0 hs-source-dirs: bench/time main-is: Main.hs build-depends: base , benchpress , conduit , deepseq , rp-tree , splitmix , splitmix-distributions , transformers , vector executable rp-tree default-language: Haskell2010 ghc-options: -threaded -O2 hs-source-dirs: app main-is: Main.hs build-depends: base , conduit , containers , rp-tree , splitmix , splitmix-distributions , transformers , vector source-repository head type: git location: https://github.com/ocramz/rp-tree