Projects: pypi: scikit-learn
https://packages.ecosyste.ms/registries/pypi.org/packages/scikit-learn
A set of python modules for machine learning and data mining
72 versions
Latest release: about 3 years ago
5,918 dependent packages
43,777,417 downloads last month
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Educational Contributors:
a.joly@ulg.ac.be
vanderplas@astro.washington.edu
bh00038@cvplws63.eps.surrey.ac.uk
ha258@cornell.edu
satra@mit.edu
zl2480@columbia.edu
pinto@alum.mit.edu
jz4721@nyu.edu
matteo.visconti.gr@dartmouth.edu
vighneshbirodkar@nyu.edu
robert.l.marchman@dartmouth.edu
rs2715@stern.nyu.edu
claire.savard@colorado.edu
aaaagrawal@iitb.ac.in
ihaque@cs.stanford.edu
rspeer@mit.edu
mluessi@nmr.mgh.harvard.edu
amitibo@tx.technion.ac.il
ericchang2017@u.northwestern.edu
jkarno@seas.upenn.edu
minghui.liu@trincoll.edu
m.lyra@sussex.ac.uk
andrew.knyazev@ucdenver.edu
lamb@cs.stanford.edu
camilo@neurostat.mit.edu
martino.sorbaro@ed.ac.uk
t.sheerman-chase@surrey.ac.uk
cgohlke@uci.edu
batulaa@drexel.edu
kcarnold@alum.mit.edu
apw@seas.harvard.edu
abie@alum.mit.edu
rossbar@berkeley.edu
alceballosa@unal.edu.co
fhoang7@berkeley.edu
hechen@seas.upenn.edu
stefan@sun.ac.za
deepyaman.datta@utexas.edu
rebekah.kim@columbia.edu
shubham.bhardwaj2015@vit.ac.in
slama@berkeley.edu
nisingh@wharton.upenn.edu
kanikas3@vt.edu
jdlabal@stanford.edu
kjells@uw.edu
markus.loning.17@ucl.ac.uk
k_nzw@klis.tsukuba.ac.jp
dkirkby@uci.edu
balawson@bu.edu
c.brummitt@columbia.edu
choo8@illinois.edu
giorgio.patrini@anu.edu.au
shangwuy@andrew.cmu.edu
rafael.possas@sydney.edu.au
olsonran@msu.edu
brian.mcfee@nyu.edu
naj273@nyu.edu
dgrusak@trinity.edu
emd222@cornell.edu
voth0@sewanee.edu
trishnendu.dd2014@cs.iiests.ac.in
apeng@berkeley.edu
boucher@cs.umass.edu
lunt@ctbp.ucsd.edu
bakhbari@mgh.harvard.edu
piraka@brandeis.edu
neal.lathia@cl.cam.ac.uk
razhoshia@post.bgu.ac.il
michal.romaniuk06@ic.ac.uk
m.batchkarov@sussex.ac.uk
lemin@cs.colostate.edu
rudvlf0413@korea.ac.kr
vredev16@msu.edu
raschkas@msu.edu
ali.baharev@univie.ac.at
a.krasoulis@sms.ed.ac.uk
arokem@berkeley.edu
gabrielvr@al.insper.edu.br
eric.sanchez1234@email.bakersfieldcollege.edu
fcchou@stanford.edu
rofuyu@cs.utexas.edu
glemaitre@visor.udg.edu
naoyaiijima@hiroshima-u.ac.jp
ayushgup@iitk.ac.in
joel@vlan-2666-10-17-16-173.staff.wireless.sydney.edu.au
jam7w2@mail.missouri.edu
j.hale09@imperial.ac.uk
tw991@nyu.edu
patel_zeel@iitgn.ac.in
vincent.lostanlen@nyu.edu
stvjc@channing.harvard.edu
ritchieng@u.nus.edu
bansalsi@usc.edu
rbarnes@umn.edu
rrohan@cs.cmu.edu
liutong.zhou@columbia.edu
mdh386@nyu.edu
mlf419@nyu.edu
shreyave@usc.edu
jin.siy@northeastern.edu
samuel_ainsworth@brown.edu
cwijes1@lsu.edu
wadawson@ucdavis.edu
xinyuliu@umich.edu
rz258@cornell.edu
daniel.mallia21@myhunter.cuny.edu
argriffi@ncsu.edu
filipj@umich.edu
kms15@case.edu
sam.dixon@berkeley.edu
khong008@e.ntu.edu.sg
jnelso11@gmu.edu
jclawton@umich.edu
jaehyunahn@sogang.ac.kr
ijpulidos@unal.edu.co
gstupp@scripps.edu
justhube@umich.edu
noamkeidar@campus.technion.ac.il
nityamd@nyu.edu
css459@nyu.edu
alyee@ucsd.edu
andersk@mit.edu
dhanus@mit.edu
coreylevinson@uchicago.edu
cailean.carter@quadram.ac.uk
bral4884@colorado.edu
dschult@colgate.edu
dpwe@ee.columbia.edu
dylan.cashman@tufts.edu
pawelsendyk@berkeley.edu
qzhang90@gatech.edu
mhaberla@calpoly.edu
saketk@student.unimelb.edu.au
eunjikim@dm.snu.ac.kr
erinrhof@uw.edu
ksivaman@purdue.edu
garmstrong@ucsd.edu
konstantin.shmelkov@polytechnique.edu
e175774@ie.u-ryukyu.ac.jp
hermidal@cs.umd.edu
jbearer@hmc.edu
jmarin@csail.mit.edu
Repository Activity:
Repository Owner:
scikit-learn (organization)
Repositories related to the scikit-learn Python machine learning library. Academic
Repositories related to the scikit-learn Python machine learning library. Academic
README Analysis:
Science Score: 100/100
Starting Score: 100 points
Bonuses:
-
+2840
Educational commit emails
142 contributors with educational email addresses -
+20
Academic repository owner
Repository owned by academic institution -
+15
Institutional repository owner
Repository owned by research institution -
+6
Science terms in README
3 scientific terms found in README
Penalties:
-
-10
PyPI ecosystem
General-purpose ecosystem
Very Likely Science (100)
Papers Mentioning scikit-learn 2,431
10.1186/s12920-020-00783-0
Predicting miRNA-disease associations using a hybrid feature representation in the heterogeneous networkCited by: 7
Author(s): Minghui Liu, Jingyi Yang, Jiacheng Wang, Lei Deng
Software Mentions: 1
Published: about 6 years ago
10.3389/fnhum.2017.00622
Quantifying the Beauty of Words: A Neurocognitive Poetics PerspectiveCited by: 25
Author(s): Arthur Jacobs
Software Mentions: 1
Published: almost 9 years ago
10.3389/fnhum.2020.00034
Predicting in vivo MRI Gradient-Field Induced Voltage Levels on Implanted Deep Brain Stimulation Systems Using Neural NetworksCited by: 2
Author(s): M. Arcan Erturk, Eric Panken, Mary Carol Conroy, Jonathan Edmonson, Jeff Kramer, Jacob Chatterton, Subharthi Banerjee
Software Mentions: 1
Published: over 6 years ago
10.1128/mSystems.01013-20
Elucidating the Regulatory Elements for Transcription Termination and Posttranscriptional Processing in the Streptomyces clavuligerus GenomeCited by: 5
Author(s): Soonkyu Hwang, Namil Lee, Donghui Choe, Yong Jae Lee, Woori Kim, Yu‐Jin Jeong, Suhyung Cho, Jaehyung Kim, Byung-Kwan Cho
Software Mentions: 1
Published: over 5 years ago
10.1371/journal.pone.0141922
Emotional Sentence Annotation Helps Predict Fiction GenreCited by: 11
Author(s): Spyridon Samothrakis, Maria Fasli
Software Mentions: 1
Published: about 11 years ago
10.3389/fimmu.2019.02454
Comparative Analysis of the CDR Loops of Antigen ReceptorsCited by: 30
Author(s): Wing Ki Wong, Jinwoo Leem, Charlotte Deane
Software Mentions: 1
Published: about 7 years ago
10.1186/s12920-018-0388-0
Min-redundancy and max-relevance multi-view feature selection for predicting ovarian cancer survival using multi-omics dataCited by: 38
Author(s): Yasser EL-Manzalawy, Tsung Yu Hsieh, Manu Shivakumar, Dokyoon Kim, Vasant Honavar
Software Mentions: 1
Published: about 8 years ago
10.3390/jpm11080748
Application of Machine Learning for Predicting Anastomotic Leakage in Patients with Gastric Adenocarcinoma Who Received Total or Proximal GastrectomyCited by: 3
Author(s): Shui-jin Shao, Lu Liu, Yufeng Zhao, Lei Mu, Qiyi Lu, Jianbing Qin
Software Mentions: 1
Published: over 5 years ago
10.3389/fimmu.2021.669357
Influence of HLA Class II Polymorphism on Predicted Cellular Immunity Against SARS-CoV-2 at the Population and Individual LevelCited by: 6
Author(s): Hannah Charlotte Copley, Loren Gragert, Andrew R. Leach, Vasilis Kosmoliaptsis
Software Mentions: 1
Published: over 5 years ago
10.1371/journal.pone.0255626
Machine learning prediction of dropping out of outpatients with alcohol use disordersCited by: 5
Author(s): So Jin Park, Sun Jung Lee, HyungMin Kim, Jae Kwon Kim, Ji Won Chun, Soo-Jung Lee, Hae Kook Lee, Daijin Kim, In Young Choi
Software Mentions: 1
Published: over 5 years ago
10.3389/fimmu.2019.02080
T-Cell Receptor Cognate Target Prediction Based on Paired α and β Chain Sequence and Structural CDR Loop SimilaritiesCited by: 37
Author(s): Esteban Lanzarotti, Paolo Marcatili, Morten Nielsen
Software Mentions: 1
Published: about 7 years ago
10.1371/journal.pone.0256648
Random forest-integrated analysis in AD and LATE brain transcriptome-wide data to identify disease-specific gene expressionCited by: 6
Author(s): Xinxing Wu, Chong Peng, Peter T. Nelson, Qiang Cheng
Software Mentions: 1
Published: about 5 years ago
10.1371/journal.pone.0251553
Artificial intelligence for classifying uncertain images by humans in determining choroidal vascular running pattern and comparisons with automated classification between artificial intelligenceCited by: 1
Author(s): Shozo Sonoda, Hideki Shiihara, Hiroto Terasaki, Naoko Kakiuchi, Ryoh Funatsu, Masatoshi Tomita, Yuki Shinohara, Eisuke Uchino, Takuma Udagawa, Guangzhou An, Masahiro Akïba, Hideo Yokota, Taiji Sakamoto
Software Mentions: 1
Published: over 5 years ago
10.1371/journal.pone.0114391
Systematic Classification of Disease Severity for Evaluation of Expanded Carrier Screening PanelsCited by: 84
Author(s): Gabriel A. Lazarin, Felicia Hawthorne, Nicholas S. Collins, E Platt, E. Edward Evans, Imran S. Haque
Software Mentions: 1
Published: almost 12 years ago
10.1371/journal.pone.0167370
A Machine Learning Approach for Using the Postmortem Skin Microbiome to Estimate the Postmortem IntervalCited by: 84
Author(s): Hunter R. Johnson, Donovan Trinidad, Stephania Guzman, Zenab Khan, James V. Parziale, Jennifer M. DeBruyn, Nathan H. Lents
Software Mentions: 1
Published: almost 10 years ago
10.1371/journal.pone.0216493
Large-area, high-resolution characterisation and classification of damage mechanisms in dual-phase steel using deep learningCited by: 42
Author(s): Carl F. Kusche, Tom Reclik, Martina Freund, Talal Al‐Samman, U. Kerzel, Sandra Korte‐Kerzel
Software Mentions: 1
Published: over 7 years ago
10.3389/fnint.2018.00054
The Varieties of the Psychedelic Experience: A Preliminary Study of the Association Between the Reported Subjective Effects and the Binding Affinity Profiles of Substituted Phenethylamines and TryptaminesCited by: 46
Author(s): Federico Zamberlán, Camila Sanz, Rocio Martínez Vivot, Carla Pallavicini, Fire Erowid, Earth Erowid, Enzo Tagliazucchi
Software Mentions: 1
Published: about 8 years ago
10.3389/fmed.2019.00255
Open Practices and Resources for Collaborative Digital PathologyCited by: 10
Author(s): Raphaël Marée
Software Mentions: 1
Published: almost 7 years ago
10.3389/fmed.2021.658665
Analysis of the Impact of Medical Features and Risk Prediction of Acute Kidney Injury for Critical Patients Using Temporal Electronic Health Record Data With Attention-Based Neural NetworkCited by: 3
Author(s): Zhimeng Chen, Ming Chen, Xu Sun, Xieli Guo, Qiuna Li, Yinqiong Huang, Yuren Zhang, Lianwei Wu, Yu Liu, Jinting Xu, Yuming Fang, Xiahong Lin
Software Mentions: 1
Published: over 5 years ago
10.1371/journal.pone.0185458
Predictors of all-cause mortality among 514,866 participants from the Korean National Health Screening CohortCited by: 14
Author(s): Cheol–Hee Ahn, Yunji Hwang, Sung Sup Park
Software Mentions: 1
Published: about 9 years ago
10.1186/s12920-018-0436-9
CRlncRC: a machine learning-based method for cancer-related long noncoding RNA identification using integrated featuresCited by: 14
Author(s): Xuan Zou, Jun Wang, Jing Li, Wen Chen, Changning Liu
Software Mentions: 1
Published: almost 8 years ago
10.3389/fmed.2021.683431
Development and Validation of Predictors for the Survival of Patients With COVID-19 Based on Machine LearningCited by: 2
Author(s): Yongfeng Zhao, Qianjun Chen, Tao Liu, Ping Luo, Yi Zhou, Minghui Liu, Bei Xiong, Fuling Zhou
Software Mentions: 1
Published: about 5 years ago
10.3389/fmicb.2020.623788
Rapid Microbial Quality Assessment of Chicken Liver Inoculated or Not With Salmonella Using FTIR Spectroscopy and Machine LearningCited by: 9
Author(s): Dimitra Dourou, Αθηνά Γρούντα, Anthoula A. Argyri, George Froutis, Panagiοtis Tsakanikas, Agapi I. Doulgeraki, Nikos Chorianopoulos, Chrysoula C. Tassou
Software Mentions: 1
Published: almost 6 years ago
10.3390/ani11010050
Determination of Body Parts in Holstein Friesian Cows Comparing Neural Networks and k Nearest Neighbour ClassificationCited by: 7
Author(s): Jennifer Salau, Jan Haas, Wolfgang Junge, Georg Thaller
Software Mentions: 1
Published: almost 6 years ago
10.3389/fmicb.2019.02582
Fourier-Transform Infrared (FTIR) Spectroscopy for Typing of Clinical Enterobacter cloacae Complex IsolatesCited by: 45
Author(s): Sophia Vogt, Kim Löffler, Ariane Dinkelacker, Birgit Bader, Ingo B. Autenrieth, Silke Peter, Jan Liese
Software Mentions: 1
Published: about 7 years ago
10.1186/s12916-020-01860-y
Development and validation of an artificial intelligence system for grading colposcopic impressions and guiding biopsiesCited by: 37
Author(s): Peng Xue, Chaohua Tang, Qing Li, Yuexiang Li, Yu Shen, Yuqian Zhao, Jiawei Chen, Jianrong Wu, Longyu Li, Wei Wang, Yucong Li, Xiaoli Cui, Shaokai Zhang, Wenhua Zhang, Xun Zhang, Kai Ma, Yefeng Zheng, Tianyi Qian, Man Tat Alexander Ng, Zhihua Liu, You‐Lin Qiao, Yu Jiang, Fen Zhao
Software Mentions: 1
Published: almost 6 years ago
10.3390/jpm11040312
Machine Learning in Prediction of IgA Nephropathy Outcome: A Comparative ApproachCited by: 6
Author(s): Andrzej Konieczny, Jakub Stojanowski, Magdalena Krajewska, Mariusz Kusztal
Software Mentions: 1
Published: over 5 years ago
10.1371/journal.pone.0171207
Data-driven system to predict academic grades and dropoutCited by: 73
Author(s): S Domínguez Rovira, Eloi Puertas, Laura Igual
Software Mentions: 1
Published: over 9 years ago
10.1371/journal.pone.0255748
Regional performance variation in external validation of four prediction models for severity of COVID-19 at hospital admission: An observational multi-centre cohort studyCited by: 2
Author(s): Kristin Wickstrøm, Valeria Vitelli, Ewan Carr, Aleksander Rygh Holten, Rebecca Bendayan, Andrew H. Reiner, Daniel Bean, Thomas Searle, Anthony Shek, Željko Kraljević, James Teo, Richard Dobson, Kristian Tonby, Alvaro Köhn‐Luque, E Amundsen
Software Mentions: 1
Published: about 5 years ago
10.1371/journal.pone.0209738
‘A world of competing sorrows’: A mixed methods analysis of media reports of children with cancer abandoning conventional treatmentCited by: 4
Author(s): Caroline Diorio, Michael Afanasiev, Kristen Salena, Stacey Marjerrison
Software Mentions: 1
Published: almost 8 years ago