机器学习:对现有算法的综合调查

Parminder Singh, Shubham Verma, Ishtiyaq Khan, Shamneesh Sharma
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引用次数: 1

摘要

机器学习是一门回顾如何利用pc来重现人类学习练习,并思考pc的自我改变技术,以获得新的信息和新的能力,区分现有的学习,并不断提高执行力和成就的学科。与人类学习相比,机器学习的适应速度更快,收集的信息更多,学习的结果传播更简单。通过这种方式,人类在机器学习领域的任何进步都会提高计算机的能力,从而影响人类文化。本文介绍了机器学习,它的基本模型和各种技术。本文还讨论了近年来在机器学习领域所做的各种研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning: A Comprehensive Survey on Existing Algorithms
Machine learning is a subject that reviews how to utilize PCs to reenact human learning exercises, and to think about self-change techniques for PCs that to get new information and new abilities, distinguish existing learning, and persistently enhance the execution and accomplishment. Contrasted with human learning, machine learning adapts speedier, the collection of information is more encourage the consequences of learning spread simpler. In this way, any advance of human in the field of machine learning will improve the ability of a computer, along these lines affect human culture. This paper introduces machine learning, its basic model, and various techniques. This paper also discusses various researches done in previous years in the field of machine learning.
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