realML

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3.0.3 realML-3.0.3-py3-none-any.whl

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Project: realML
Version: 3.0.3
Filename: realML-3.0.3-py3-none-any.whl
Download: [link]
Size: 100181
MD5: 5e4e3992ff85cbeef9b94dbab23dbf2d
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Uploaded: 2022-03-21 15:49:29 +0000

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METADATA

Metadata-Version: 2.1
Name: realML
Version: 3.0.3
Summary: ICSI provided machine learning primitives for DARPA D3M project, focusing on fast kernel methods and matrix factorizations
Author: International Computer Science Institute
Author-Email: gittea[at]rpi.edu
Home-Page: https://gitlab.com/datadrivendiscovery/contrib/realML
License: Apache License 2.0
Keywords: d3m_primitive,machine learning,regression,dimensionality reduction,low rank factorization,featurization,sufficient dimensionality reduction,kernel methods
Requires-Dist: numpy (>=1.14.0)
Requires-Dist: regex (>=2017.4.5)
Requires-Dist: scikit-learn (>=0.18.1)
Requires-Dist: scipy (>=1.2.1)
Description-Content-Type: text/markdown
[Description omitted; length: 334 characters]

WHEEL

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Tag: py3-none-any

RECORD

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top_level.txt

realML

entry_points.txt

feature_extraction.pca_features.RandomizedPolyPCA = realML.matrix:RandomizedPolyPCA
feature_extraction.sparse_pca.RobustSparsePCA = realML.matrix:RobustSparsePCA
feature_extraction.sparse_pca.SparsePCA = realML.matrix:SparsePCA
regression.rfm_precondition_ed_gaussian_krr.RFMPreconditionedGaussianKRR = realML.kernel:RFMPreconditionedGaussianKRR
regression.rfm_precondition_ed_polynomial_krr.RFMPreconditionedPolynomialKRR = realML.kernel:RFMPreconditionedPolynomialKRR
regression.tensor_machines_regularized_least_squares.TensorMachinesRegularizedLeastSquares = realML.kernel:TensorMachinesRegularizedLeastSquares