Result for 0C165A95DAB1FAA5C8754118711D9BF82B66BDED

Query result

Key Value
FileName./usr/include/tapkee/routines/manifold_sculpting.hpp
FileSize12497
MD50ED3267F9DE43F80E63F725491A2695A
SHA-10C165A95DAB1FAA5C8754118711D9BF82B66BDED
SHA-25660E28B394195FB264BC5D759371F92E40E74E380FE4DD0AD0B6B94A1C7981037
SSDEEP384:hf/W6Ft9x98hNeKtlSUjji37m9saKdMA8Kd:hX798hNeKtlSUj4S9saU58Kd
TLSHT1B54264B4F32C091BFAA021E3E5059AADC9ABD5E2F5E15C62FC9C606073C080ADB3D354
hashlookup:parent-total37
hashlookup:trust100

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Parents (Total: 37)

The searched file hash is included in 37 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5985F905EB488F64647F841E671DCF8F6
PackageArchnoarch
PackageDescriptionTapkee is a C++ template library for dimensionality reduction with some bias on spectral methods. The Tapkee origins from the code developed during GSoC 2011 as the part of the Shogun machine learning toolbox. The project aim is to provide efficient and flexible standalone library for dimensionality reduction which can be easily integrated to existing codebases. Tapkee leverages capabilities of effective Eigen3 linear algebra library and optionally makes use of the ARPACK eigensolver. The library uses CoverTree and VP-tree data-structures to compute nearest neighbors. To achieve greater flexibility we provide a callback interface which decouples dimension reduction algorithms from the data representation and storage schemes. Tapkee provides implementations of the following dimension reduction methods: * Locally Linear Embedding and Kernel Locally Linear Embedding (LLE/KLLE) * Neighborhood Preserving Embedding (NPE) * Local Tangent Space Alignment (LTSA) * Linear Local Tangent Space Alignment (LLTSA) * Hessian Locally Linear Embedding (HLLE) * Laplacian eigenmaps * Locality Preserving Projections * Diffusion map * Isomap and landmark Isomap * Multidimensional scaling and landmark Multidimensional scaling (MDS/lMDS) * Stochastic Proximity Embedding (SPE) * PCA and randomized PCA * Kernel PCA (kPCA) * Random projection * Factor analysis * t-SNE * Barnes-Hut-SNE
PackageMaintainerFedora Project
PackageNametapkee-devel
PackageRelease6.fc24
PackageVersion1.0
SHA-1096ADC455DCDD18882895C0053AC21CCBB46B6E4
SHA-2566614BCF50CF7A1D9DF0FFCCE48F4DF68FF161C41602C09B630847F2BE2613FDC
Key Value
MD50025AD59E690306FE4EEFCA726C9E8F2
PackageArchppc64le
PackageDescriptionThis package provides debug information for package tapkee. Debug information is useful when developing applications that use this package or when debugging this package.
PackageMaintainerFedora Project
PackageNametapkee-debuginfo
PackageRelease3.fc22
PackageVersion1.0
SHA-10CA05D2CF0184A71EA92647450172FBE634DDE12
SHA-256712B61558E10CA99967B458CADEF730724BB1247F018A903329567F8B6BB5C2B
Key Value
MD53240C15667DA078EF8EE7311C70BDA2C
PackageArchppc64
PackageDescriptionThis package provides debug information for package tapkee. Debug information is useful when developing applications that use this package or when debugging this package.
PackageMaintainerFedora Project
PackageNametapkee-debuginfo
PackageRelease3.fc21
PackageVersion1.0
SHA-11693CBD918D96FC62AD336BF0A84DE1921BF209D
SHA-25606A41A94C4C5AA6BC2CCA8B05C80E8FA29E7BEDF88D3472875FCAF441BD283BC
Key Value
MD5D109A3B0490E41B1AEEDD7F6813DAD40
PackageArchx86_64
PackageDescriptionThis package provides debug information for package tapkee. Debug information is useful when developing applications that use this package or when debugging this package.
PackageMaintainerFedora Project
PackageNametapkee-debuginfo
PackageRelease2.el7
PackageVersion1.1
SHA-1183AEC99144D278C39ACDF56097E60F24A67A438
SHA-2563C195437BEDF258C1962C78852AA0011C60CC5A3247075C5DB99FBBB2C9AE326
Key Value
MD589A2BB1637C591F276519840B0FDEB05
PackageArchnoarch
PackageDescriptionTapkee is a C++ template library for dimensionality reduction with some bias on spectral methods. The Tapkee origins from the code developed during GSoC 2011 as the part of the Shogun machine learning toolbox. The project aim is to provide efficient and flexible standalone library for dimensionality reduction which can be easily integrated to existing codebases. Tapkee leverages capabilities of effective Eigen3 linear algebra library and optionally makes use of the ARPACK eigensolver. The library uses CoverTree and VP-tree data-structures to compute nearest neighbors. To achieve greater flexibility we provide a callback interface which decouples dimension reduction algorithms from the data representation and storage schemes. Tapkee provides implementations of the following dimension reduction methods: * Locally Linear Embedding and Kernel Locally Linear Embedding (LLE/KLLE) * Neighborhood Preserving Embedding (NPE) * Local Tangent Space Alignment (LTSA) * Linear Local Tangent Space Alignment (LLTSA) * Hessian Locally Linear Embedding (HLLE) * Laplacian eigenmaps * Locality Preserving Projections * Diffusion map * Isomap and landmark Isomap * Multidimensional scaling and landmark Multidimensional scaling (MDS/lMDS) * Stochastic Proximity Embedding (SPE) * PCA and randomized PCA * Kernel PCA (kPCA) * Random projection * Factor analysis * t-SNE * Barnes-Hut-SNE
PackageMaintainerFedora Project
PackageNametapkee-devel
PackageRelease3.fc21
PackageVersion1.0
SHA-11FC7803F82A70E0F6EF722F6DBC1903403C3D6E9
SHA-2562F11CC7925AADB52FC5EC712A9C0D2D60A895D711844FC91B4A15CD7575F29E0
Key Value
MD56C88DD88E14EA71665ED6F29F8342E5A
PackageArchnoarch
PackageDescriptionTapkee is a C++ template library for dimensionality reduction with some bias on spectral methods. The Tapkee origins from the code developed during GSoC 2011 as the part of the Shogun machine learning toolbox. The project aim is to provide efficient and flexible standalone library for dimensionality reduction which can be easily integrated to existing codebases. Tapkee leverages capabilities of effective Eigen3 linear algebra library and optionally makes use of the ARPACK eigensolver. The library uses CoverTree and VP-tree data-structures to compute nearest neighbors. To achieve greater flexibility we provide a callback interface which decouples dimension reduction algorithms from the data representation and storage schemes. Tapkee provides implementations of the following dimension reduction methods: * Locally Linear Embedding and Kernel Locally Linear Embedding (LLE/KLLE) * Neighborhood Preserving Embedding (NPE) * Local Tangent Space Alignment (LTSA) * Linear Local Tangent Space Alignment (LLTSA) * Hessian Locally Linear Embedding (HLLE) * Laplacian eigenmaps * Locality Preserving Projections * Diffusion map * Isomap and landmark Isomap * Multidimensional scaling and landmark Multidimensional scaling (MDS/lMDS) * Stochastic Proximity Embedding (SPE) * PCA and randomized PCA * Kernel PCA (kPCA) * Random projection * Factor analysis * t-SNE * Barnes-Hut-SNE
PackageMaintainerFedora Project
PackageNametapkee-devel
PackageRelease2.el7
PackageVersion1.1
SHA-1233E1FF4B960B84281649C9D7762711E4A45E2B7
SHA-25639C283D96740071F4111C64DCDD6319D2C95BF07ACBC498289D77D1D401E2B38
Key Value
MD5B0F1215417E2F3FD2AD67F182BD0F0CE
PackageArchs390
PackageDescriptionThis package provides debug information for package tapkee. Debug information is useful when developing applications that use this package or when debugging this package.
PackageMaintainerFedora Project
PackageNametapkee-debuginfo
PackageRelease5.fc23
PackageVersion1.0
SHA-123AED53DF5200B6EDCC70F3B4971464D505D4778
SHA-256462A6D27ECFB2F4B3CCA6B7603551978B467EF91EC07C676D59BF95AB1B968A5
Key Value
MD5D6BC55AF6175A19DB531F98501489B54
PackageArchnoarch
PackageDescriptionTapkee is a C++ template library for dimensionality reduction with some bias on spectral methods. The Tapkee origins from the code developed during GSoC 2011 as the part of the Shogun machine learning toolbox. The project aim is to provide efficient and flexible standalone library for dimensionality reduction which can be easily integrated to existing codebases. Tapkee leverages capabilities of effective Eigen3 linear algebra library and optionally makes use of the ARPACK eigensolver. The library uses CoverTree and VP-tree data-structures to compute nearest neighbors. To achieve greater flexibility we provide a callback interface which decouples dimension reduction algorithms from the data representation and storage schemes. Tapkee provides implementations of the following dimension reduction methods: * Locally Linear Embedding and Kernel Locally Linear Embedding (LLE/KLLE) * Neighborhood Preserving Embedding (NPE) * Local Tangent Space Alignment (LTSA) * Linear Local Tangent Space Alignment (LLTSA) * Hessian Locally Linear Embedding (HLLE) * Laplacian eigenmaps * Locality Preserving Projections * Diffusion map * Isomap and landmark Isomap * Multidimensional scaling and landmark Multidimensional scaling (MDS/lMDS) * Stochastic Proximity Embedding (SPE) * PCA and randomized PCA * Kernel PCA (kPCA) * Random projection * Factor analysis * t-SNE * Barnes-Hut-SNE
PackageMaintainerFedora Project
PackageNametapkee-devel
PackageRelease3.fc21
PackageVersion1.0
SHA-123F518AF8636F0A389D487BCBC63D13977CC8FF2
SHA-256D9E068E75E45305FEB3388C96D95D4F1B9C880AE59B9A305A036176C9D05CCA8
Key Value
MD556AB4FB085399BD298F5B20CEE745E1A
PackageArchnoarch
PackageDescriptionTapkee is a C++ template library for dimensionality reduction with some bias on spectral methods. The Tapkee origins from the code developed during GSoC 2011 as the part of the Shogun machine learning toolbox. The project aim is to provide efficient and flexible standalone library for dimensionality reduction which can be easily integrated to existing codebases. Tapkee leverages capabilities of effective Eigen3 linear algebra library and optionally makes use of the ARPACK eigensolver. The library uses CoverTree and VP-tree data-structures to compute nearest neighbors. To achieve greater flexibility we provide a callback interface which decouples dimension reduction algorithms from the data representation and storage schemes. Tapkee provides implementations of the following dimension reduction methods: * Locally Linear Embedding and Kernel Locally Linear Embedding (LLE/KLLE) * Neighborhood Preserving Embedding (NPE) * Local Tangent Space Alignment (LTSA) * Linear Local Tangent Space Alignment (LLTSA) * Hessian Locally Linear Embedding (HLLE) * Laplacian eigenmaps * Locality Preserving Projections * Diffusion map * Isomap and landmark Isomap * Multidimensional scaling and landmark Multidimensional scaling (MDS/lMDS) * Stochastic Proximity Embedding (SPE) * PCA and randomized PCA * Kernel PCA (kPCA) * Random projection * Factor analysis * t-SNE * Barnes-Hut-SNE
PackageMaintainerFedora Project
PackageNametapkee-devel
PackageRelease5.fc23
PackageVersion1.0
SHA-12DF3CF8071268FBDF482DD310592237A7835D7BE
SHA-256FD42B6EC5EE63C089561DBFCA8F9E7D525BCB73D3F989E1821527FB717779A9A
Key Value
MD5CFCA6F0ED66B517E3636EF86C246A4D2
PackageArchaarch64
PackageDescriptionThis package provides debug information for package tapkee. Debug information is useful when developing applications that use this package or when debugging this package.
PackageMaintainerFedora Project
PackageNametapkee-debuginfo
PackageRelease3.fc21
PackageVersion1.0
SHA-12FD8EFE82BAFAFECE55AE4DCF9C7A4FF85BD498A
SHA-2568373480804D97396293AF1980AE674FD662CDE357A26D2992EC5831C2FBA71E8