Parents (Total: 6)

The searched file hash is included in 6 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	5110065B124E0FEBFC3B2E038BDD3D1B
PackageArch	x86_64
PackageDescription	Tapkee is a cli-tool for efficient dimension reduction and 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
PackageMaintainer	Fedora Project
PackageName	tapkee-cli
PackageRelease	2.el7
PackageVersion	1.1
SHA-1	43479A97834AAD1F36F622B560255705404F0C17
SHA-256	FE49EA71C7ACA1C90B99A9726495C2922EFEF4735049E1D7631E3C93E642FB3C

Key	Value
MD5	F0730CFFA7BE0C05DA0661C484A54903
PackageArch	noarch
PackageDescription	This package contains the documentation files and some brief examples for tapkee.
PackageMaintainer	Fedora Project
PackageName	tapkee-doc
PackageRelease	2.el7
PackageVersion	1.1
SHA-1	DB50259E1764AC6C768548DEBCABF4A0CA11F406
SHA-256	A2256B8BBB87E1CDD89BD208FFFB4A840D5F188D5EAA743966F5F5BB5906F969

Key	Value
MD5	105DD28D3E3701B0332197FD8509331B
PackageArch	aarch64
PackageDescription	Tapkee is a cli-tool for efficient dimension reduction and 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
PackageMaintainer	Fedora Project
PackageName	tapkee-cli
PackageRelease	2.el7
PackageVersion	1.1
SHA-1	0D41B1A701E734D3522E1B1EE5282ADC2BD506DD
SHA-256	8B8D14036F83CEA93E1999E5A37E917F0151724E3B312E20F694E581F41DFF4F

Key	Value
MD5	150855F987D47D91DE592B1E5E141FBC
PackageArch	ppc64le
PackageDescription	Tapkee is a cli-tool for efficient dimension reduction and 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
PackageMaintainer	Fedora Project
PackageName	tapkee-cli
PackageRelease	2.el7
PackageVersion	1.1
SHA-1	C5B18389D1DCF504657780E3A598CDC26FC3275B
SHA-256	B53DA0CB457489CBAE82A2F9DF99DBC00B7CABB7723E2B7EF1D76AA317D22B12

Key	Value
MD5	B733D7FD3E59539DF91F80451060B767
PackageArch	ppc64
PackageDescription	Tapkee is a cli-tool for efficient dimension reduction and 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
PackageMaintainer	Fedora Project
PackageName	tapkee-cli
PackageRelease	2.el7
PackageVersion	1.1
SHA-1	1CE0C67C0BE5CCC04B01504E553EDB24CC382990
SHA-256	780FB365227E292FB2542CF6D1ACC6AF3DBE74298333F0D2A9EED1CB64A749D7

Key	Value
MD5	6C88DD88E14EA71665ED6F29F8342E5A
PackageArch	noarch
PackageDescription	Tapkee 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
PackageMaintainer	Fedora Project
PackageName	tapkee-devel
PackageRelease	2.el7
PackageVersion	1.1
SHA-1	233E1FF4B960B84281649C9D7762711E4A45E2B7
SHA-256	39C283D96740071F4111C64DCDD6319D2C95BF07ACBC498289D77D1D401E2B38