Ecosyste.ms: Papers

An open API service providing mapping between scientific papers and software projects that are mentioned in them.
All mentions data is based on the CZI Software Mentions dataset.

Projects: cran: evtree

https://packages.ecosyste.ms/registries/cran.r-project.org/packages/evtree

Evolutionary Learning of Globally Optimal Trees
15 versions
Latest release: over 5 years ago
9 dependent packages
1,681 downloads last month

Papers Mentioning evtree 6

Interpretability Versus Accuracy: A Comparison of Machine Learning Models Built Using Different Algorithms, Performance Measures, and Features to Predict E. coli Levels in Agricultural Water
Cited by: 12
Author(s): Daniel Weller, Tanzy Love, Martin Wiedmann
Software Mentions: 16
Published: over 3 years ago

10.3389/fsufs.2020.561517

Predictive Models May Complement or Provide an Alternative to Existing Strategies for Assessing the Enteric Pathogen Contamination Status of Northeastern Streams Used to Provide Water for Produce Production
Cited by: 19
Author(s): Daniel Weller, Tanzy Love, Alexandra Belias, Martin Wiedmann
Software Mentions: 12
Published: about 4 years ago

10.2196/17110

Predicting Metabolic Syndrome With Machine Learning Models Using a Decision Tree Algorithm: Retrospective Cohort Study
Cited by: 26
Author(s): Cheng Yu, Yu Lin, Chang Hsien Lin, Sen Te Wang, Shiyng Yu Lin, Sanders H. Lin, Jenny L Wu, Shy Shin Chang
Software Mentions: 7
Published: over 4 years ago

10.3390/tomography7030031

Combination of Radiomics and Machine Learning with Diffusion-Weighted MR Imaging for Clinical Outcome Prognostication in Cervical Cancer
Cited by: 11
Author(s): Ankush Jajodia, Ayushi Gupta, Helmut Prosch, Marius E. Mayerhoefer, Swarupa Mitra, Sunil Pasricha, Anurag Mehta, Sunil K. Puri, Arvind Chaturvedi
Software Mentions: 3
Published: over 3 years ago

10.7717/peerj.3289

Network science meets respiratory medicine for OSAS phenotyping and severity prediction
Cited by: 24
Author(s): Ștefan Mihăicuță, Mihai Udrescu, Alexandru Topîrceanu, Lucreţia Udrescu
Software Mentions: 1
Published: over 7 years ago

10.1371/journal.pone.0239779

Maternal serum concentration of anti-Müllerian hormone is a better predictor than basal follicle stimulating hormone of successful blastocysts development during IVF treatment
Cited by: 5
Author(s): S. Sadruddin, B.D. Barnett, L.T. Ku, Dara Havemann, Sara J. Mucowski, Richard Herrington, Warren W. Burggren
Software Mentions: 1
Published: about 4 years ago