Semantic Scholar Open Access 2011 87524 sitasi

Scikit-learn: Machine Learning in Python

Fabian Pedregosa G. Varoquaux Alexandre Gramfort V. Michel B. Thirion +12 lainnya

Abstrak

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic and commercial settings. Source code, binaries, and documentation can be downloaded from http://scikit-learn.sourceforge.net.

Topik & Kata Kunci

Computer Science

Penulis (17)

Fabian Pedregosa

G. Varoquaux

Alexandre Gramfort

V. Michel

B. Thirion

O. Grisel

Mathieu Blondel

Gilles Louppe

P. Prettenhofer

Ron Weiss

Ron J. Weiss

J. Vanderplas

Alexandre Passos

D. Cournapeau

M. Brucher

M. Perrot

E. Duchesnay

Format Sitasi

APA MLA BibTeX

Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O. et al. (2011). Scikit-learn: Machine Learning in Python. https://doi.org/10.5555/1953048.2078195

Akses Cepat

PDF tidak tersedia langsung

Cek di sumber asli →

Lihat di Sumber doi.org/10.5555/1953048.2078195

Informasi Jurnal

Tahun Terbit: 2011
Bahasa: en
Total Sitasi: 87524×
Sumber Database: Semantic Scholar
DOI: 10.5555/1953048.2078195
Akses: Open Access ✓