Critical power prediction using SVM algorithms-Reference-Cited by-同舟云学术

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Critical power prediction using SVM algorithms

Published:2020 Issue: Volume:169 Page:198-202
ISSN:1877-0509
Container-title:Procedia Computer Science
language:en
Short-container-title:Procedia Computer Science

Author:

Ryabtseva Viktoria,Skomorokhov Alexander

Publisher

Elsevier BV

Subject

General Engineering

Reference11 articles.

1. Anaconda Distribution,. URL: https://www.anaconda.com/.

2. Bzdok, D., Krzywinski, M., Altman, N., 2018. Points of significance: Machine learning: supervised methods.

3. Dyalog,. URL: https://www.dyalog.com/.

4. Introduction to machine learning with Python: a guide for data scientists;Müller,2016

5. Scikit-learn: Machine learning in python;Pedregosa;Journal of machine learning research,2011

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