API design for machine learning software: experiences from the scikit-learn project

2013 · arXiv (Cornell University) · 1,804 citations · 1 from inside this corpus

Lars Buitinck low, Gilles Louppe, Mathieu Blondel, Fabián Pedregosa, Andreas Mueller, Olivier Grisel, Vlad Niculae low, Peter Prettenhofer, Alexandre Gramfort, Jaques Grobler low, Robert Layton, Jake Vanderplas, Arnaud Joly low, Brian Holt low

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

5 of 5 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.

this paper works it cites works citing it node size = global citations · hover for the full title

What this paper cites, inside the corpus

Paper	Year	Cited
Scikit-learn: Machine Learning in Python	2012	64,025
Matplotlib: A 2D Graphics Environment	2007	40,822
IPython: A System for Interactive Scientific Computing	2007	4,205
Software Framework for Topic Modelling with Large Corpora	2010	3,809

What cites it, inside the corpus

Paper	Year	Cited
CatBoost for big data: an interdisciplinary review	2020	1,776

Links

Open access copy · OpenAlex record

Topics

Computational Physics and Python Applications	Computer Science
Machine Learning and Data Classification	Computer Science
Scientific Computing and Data Management	Decision Sciences

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

supports14 author record(s) attached.
supports18 reference(s) recorded.
neutralThe DOI carries no year to check against.
supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:53+00:00.

sha256 db1645b78a57e29a…