找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: An Introduction to Machine Learning; Miroslav Kubat Textbook 20172nd edition Springer International Publishing AG 2017 Bayesian classifier

[复制链接]
查看: 19879|回复: 59
发表于 2025-3-21 16:12:20 | 显示全部楼层 |阅读模式
期刊全称An Introduction to Machine Learning
影响因子2023Miroslav Kubat
视频video
发行地址Offers frequent opportunities to practice techniques with control questions, exercises, thought experiments, and computer assignments..Reinforces principles using well-selected toy domains and relevan
图书封面Titlebook: An Introduction to Machine Learning;  Miroslav Kubat Textbook 20172nd edition Springer International Publishing AG 2017 Bayesian classifier
影响因子.This textbook presents fundamental machine learning concepts in an easy to understand manner by providing practical advice, using straightforward examples, and offering engaging discussions of relevant applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to combine these simple tools by way of “boosting,” how to exploit them in more complicated domains, and how to deal with diverse advanced practical issues. One chapter is dedicated to the popular genetic algorithms.. .This revised edition contains three entirely new chapters on critical topics regarding the pragmatic application of machine learning in industry. The chapters examine multi-label domains, unsupervised learning and its use in deep learning, and logical approaches to induction. Numerous chapters have been expanded, and the presentation of the material has been enhanced. The book contains many new exercises, numerous solved examples, thought-provoking experiments, and computer assignments for independent work..
Pindex Textbook 20172nd edition
The information of publication is updating

书目名称An Introduction to Machine Learning影响因子(影响力)




书目名称An Introduction to Machine Learning影响因子(影响力)学科排名




书目名称An Introduction to Machine Learning网络公开度




书目名称An Introduction to Machine Learning网络公开度学科排名




书目名称An Introduction to Machine Learning被引频次




书目名称An Introduction to Machine Learning被引频次学科排名




书目名称An Introduction to Machine Learning年度引用




书目名称An Introduction to Machine Learning年度引用学科排名




书目名称An Introduction to Machine Learning读者反馈




书目名称An Introduction to Machine Learning读者反馈学科排名




单选投票, 共有 0 人参与投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用户组没有投票权限
发表于 2025-3-21 23:59:01 | 显示全部楼层
发表于 2025-3-22 00:42:26 | 显示全部楼层
发表于 2025-3-22 05:29:04 | 显示全部楼层
Die Unbeherrschtheit bei Platon in machine learning, too. A group of classifiers is created in a way that makes each of them somewhat different. When they vote about the recommended class, their “collective wisdom” often compensates for each individual’s imperfections.
发表于 2025-3-22 10:17:47 | 显示全部楼层
发表于 2025-3-22 13:35:04 | 显示全部楼层
发表于 2025-3-22 17:21:22 | 显示全部楼层
发表于 2025-3-22 22:13:03 | 显示全部楼层
发表于 2025-3-23 01:53:38 | 显示全部楼层
Induction of Voting Assemblies, in machine learning, too. A group of classifiers is created in a way that makes each of them somewhat different. When they vote about the recommended class, their “collective wisdom” often compensates for each individual’s imperfections.
发表于 2025-3-23 06:31:14 | 显示全部楼层
Performance Evaluation, simple. Error rate rarely paints the whole picture, and there are situations in which it can even be misleading. This is why the conscientious engineer wants to be acquainted with other criteria to assess the classifiers’ performance. This knowledge will enable her to choose the one that is best in capturing the behavioral aspects of interest.
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-19 22:55
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表