An empirical comparison of supervised machine learning techniques in bioinformatics

机译：有监督的机器学习技术在生物信息学中的经验比较

获取原文

获取原文并翻译 | 示例

页面导航

摘要
著录项
相似文献
相关主题

摘要

Research in bioinformatics is driven by the experimental data. Current biological databases are populated by vast amounts of experimental data. Machine learning has been widely applied to bioinformatics and has gained a lot of success in this research area. At present, with various learning algorithms available in the literature, researchers are facing difficulties in choosing the best method that can apply to their data. We performed an empirical study on 7 individual learning systems and 9 different combined methods on 4 different biological data sets, and provide some suggested issues to be considered when answering the following questions: (ⅰ) How does one choose which algorithm is best suitable for their data set? (ⅱ) Are combined methods better than a single approach? (ⅲ) How does one compare the effectiveness of a particular algorithm to the others?

机译：生物信息学的研究是由实验数据驱动的。当前的生物学数据库充斥着大量的实验数据。机器学习已被广泛应用于生物信息学，并在该研究领域获得了很多成功。目前，由于文献中提供了各种学习算法，研究人员在选择可应用于其数据的最佳方法时面临着困难。我们对4种不同的生物学数据集上的7种个体学习系统和9种不同的组合方法进行了实证研究，并提供了一些建议的问题，以便回答以下问题：（ⅰ）如何选择最适合其算法的算法数据集？（ⅱ）组合方法是否比单一方法更好？（ⅲ）如何将一种特定算法的有效性与其他算法进行比较？

著录项

来源
《Asia-Pacific Bioinformatics Conference(APBC 2003); 200302; Adelaide(AU)》|2003年|P.219-222|共4页
会议地点 Adelaide(AU)
作者
Aik Choon TAN; David GILBERT;
展开▼
作者单位

Bioinformatics Research Centre, Department of Computing Science 12 Lilybank Gardens, University of Glasgow, Glasgow G12 8QQ, UK;

展开▼
会议组织
原文格式 PDF
正文语种 eng
中图分类生物工程学（生物技术）;
关键词
supervised machine learning; bioinformatics; ensemble methods; performance evaluation;

机译：监督机器学习;生物信息学;集成方法;性能评估;

相似文献

外文文献
中文文献
专利

1. Comparison of supervised machine learning classification techniques in prediction of locoregional recurrences in early oral tongue cancer [J] . International journal of medical informatics . 2020,第Apra期

机译：有监督的机器学习分类技术在预测早期口腔癌局部复发中的比较
2. Comparison of supervised machine learning techniques for customer churn prediction based on analysis of customer behavior [J] . Khodabandehlou Samira, Zivari Rahman Mahmoud Journal of systems and information technology . 2017,第1a2期

机译：基于客户行为分析的有监督机器学习技术对客户流失预测的比较
3. An empirical comparison of machine learning techniques for dam behaviour modelling (vol 56, pg 9, 2015) [J] . Salazar F., Toledo M. A., Onate E., Structural Safety . 2016,第期

机译：大坝行为建模的机器学习技术的经验比较（第56卷，第9页，2015年）
4. An empirical comparison of supervised machine learning techniques in bioinformatics [C] . Aik Choon Tan, David Gilbert, PDavid Gilbert Proceedings of the First Asia-Pacific bioinformatics conference on Bioinformatics 2003 . 2003

机译：有监督的机器学习技术在生物信息学中的经验比较
5. Semi-Supervised Machine Learning Techniques for Classification of Evolving Data in Pattern Recognition =TECHNIQUES SEMI-SUPERVISéES D'APPRENTISSAGE MACHINE POUR LA CLASSIFICATION DES DONNéES EN éVOLUTION EN RECONNAISSANCE DE FORMES [D] . Tencer, Lukas. 2017

机译：半监督机器学习技术，用于模式识别中不断发展的数据分类=在表单识别中对数据进行分类的半监督机器学习技术
6. Supervised Machine Learning Algorithms for Bioelectromagnetics: Prediction Models and Feature Selection Techniques Using Data from Weak Radiofrequency Radiation Effect on Human and Animals Cells [O] . Malka N. Halgamuge 2020

机译：生物电磁学的有监督机器学习算法：使用弱射频辐射对人和动物细胞的数据预测模型和特征选择技术
7. Comparison of supervised machine learning classification techniques in prediction of locoregional recurrences in early oral tongue cancer [O] . Rasheed Omobolaji Alabi, Mohammed Elmusrati, Iris Sawazaki‐Calone, 2020

机译：监督机床学习分类技术对早期口腔舌癌课程复发预测的比较

An empirical comparison of supervised machine learning techniques in bioinformatics

摘要

著录项

相似文献

相关主题

期刊订阅