Data on Machine Learning Detailed by Researchers at Department of Computer Appli cations (Optifeat: Enhancing Feature Selection, a Hybrid Approach Combining Subj ect Matter Expertise and Recursive Feature Elimination Method)

计算机应用系研究人员详细介绍的机器学习数据（Optifeat：增强特征选择，一种结合子领域专业知识和递归特征消除方法的混合方法）

Robotics & Machine Learning Daily News2024，Issue(Dec.6) ：113-114.

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Data on Machine Learning Detailed by Researchers at Department of Computer Appli cations (Optifeat: Enhancing Feature Selection, a Hybrid Approach Combining Subj ect Matter Expertise and Recursive Feature Elimination Method)

计算机应用系研究人员详细介绍的机器学习数据（Optifeat：增强特征选择，一种结合子领域专业知识和递归特征消除方法的混合方法）

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-机器学习的新研究是一篇报道的主题。据新闻报道NewsRx记者在印度密苏鲁的报道中指出，“优化业绩”Java虚拟机器(JVMs)(Sahin等人，在Proc IEEE Int Congr Big Data Congr 410-417中，2016)是实现Java应用程序高效执行的关键。在确定用于微调jvm的最相关参数方面的作用，从而增强jvm的总体效率。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Machine Learning is th e subject of a report. According to newsreporting originating in Mysuru, India, by NewsRx journalists, research stated, “Optimizing the performanceof Java Vir tual Machines (JVMs) (Sahin et al. in Proc IEEE Int Congr Big Data BigData Congr 410-417,2016) is crucial for achieving efficient execution of Java application s. Feature selection plays a pivotalrole in identifying the most relevant param eters for fine-tuning JVMs, thereby enhancing their overallefficiency.”

Key words

Mysuru/India/Asia/Cyborgs/Emerging T echnologies/Machine Learning/Department of Computer Applications

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出版年

2024

Robotics & Machine Learning Daily News

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