机器学习
人工智能
计算机科学
无监督学习
在线机器学习
基于实例的学习
计算学习理论
半监督学习
唤醒睡眠算法
学习分类器系统
超启发式
主动学习(机器学习)
算法
机器人学习
监督学习
强化学习
加权多数算法
人工神经网络
泛化误差
机器人
移动机器人
作者
Vratika Gupta,Vinay Kumar Mishra,Priyank Singhal,Amit Kumar
标识
DOI:10.1109/smart55829.2022.10047618
摘要
Machine learning is a subset of Artificial intelligence. Algorithms for machine learning automatically learn from experience and improve from it without being explicitly programmed. Machine learning defines Supervised, Unsupervised and Reinforcement Learning. Supervised algorithms are worked on under guidance but unsupervised algorithms are worked on without guidance. Machine learning provides good accuracy in both the algorithms. This paper is describing machine learning methods, different types of supervised learning algorithms, comparison of machine learning algorithms and application of machine learning algorithms.
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