Result: metric-learn: Metric Learning Algorithms in Python

Title:
metric-learn: Metric Learning Algorithms in Python
Authors:
de Vazelhes, William, Carey, Cj, Tang, Yuan, Vauquier, Nathalie, Bellet, Aurélien
Contributors:
Machine Learning in Information Networks (MAGNET), Centre Inria de l'Université de Lille, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Google Inc., Ant Financial
Publisher Information:
CCSD, 2019.
Publication Year:
2019
Collection:
collection:CNRS
collection:INRIA
collection:INRIA-LILLE
collection:INRIA_TEST
collection:TESTALAIN1
collection:CRISTAL
collection:INRIA2
collection:CRISTAL-MAGNET
collection:UNIV-LILLE
collection:TEST-HALCNRS
collection:INRIA-ETATSUNIS
Subject Terms:
Machine Learning, Python, Metric Learning, Scikit-learn, [INFO.INFO-LG]Computer Science [cs], Machine Learning [cs.LG], [STAT.ML]Statistics [stat], Machine Learning [stat.ML], [INFO.INFO-SE]Computer Science [cs], Software Engineering [cs.SE]
Original Identifier:
ARXIV: 1908.04710
HAL: hal-02376986
Document Type:
Electronic Resource preprint<br />Preprints<br />Working Papers
Language:
English
Relation:
info:eu-repo/semantics/altIdentifier/arxiv/1908.04710
Access URL:
https://inria.hal.science/hal-02376986
https://inria.hal.science/hal-02376986v1/document
https://inria.hal.science/hal-02376986v1/file/1908.04710.pdf
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edshal.hal.02376986v1
Database:
HAL

Further Information

GitHub repository: https://github.com/scikit-learn-contrib/metric-learn
metric-learn is an open source Python package implementing supervised and weakly-supervised distance metric learning algorithms. As part of scikit-learn-contrib, it provides a unified interface compatible with scikit-learn which allows to easily perform cross-validation, model selection, and pipelining with other machine learning estimators. metric-learn is thoroughly tested and available on PyPi under the MIT licence.