Lessons learned from the application of machine learning to studies on plant response to radio-frequency-Reference-Cited by-同舟云学术

Lessons learned from the application of machine learning to studies on plant response to radio-frequency

Published:2019-11 Issue: Volume:178 Page:108634
ISSN:0013-9351
Container-title:Environmental Research
language:en
Short-container-title:Environmental Research

Author:

Halgamuge Malka N.,Davis Devra

Publisher

Elsevier BV

Subject

General Environmental Science,Biochemistry

Reference22 articles.

1. Some effects of weak magnetic fields on biological systems: Rf fields can change radical concentrations and cancer cell growth rates;Barnes;IEEE Power Electron,2016

2. Random forests;Breiman;Mach. Learn.,2001

3. Random Forest versus Logistic Regression: a Large-Scale Benchmark Experiment, Technical Report Number 205;Couronne,2017

4. Data Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data;Dietrich,2015

5. Uncertainty analysis of selected sources of errors in bioelectromagnetic investigations;Dlugosz,2013

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