Machine Learning
—grew out of work in AI
—new capability for computers
Examples:
--Database mining
large datasets from growth of automation/web.
E.g, Web click data, medical records, biology, enginerring
--Application can't program by hand.
E.g, autonomous helicopter, handwriting recognization,
Natural Language Processing(NLP),Computer vision.
--Self-customizing programs
E.g, Amazon, Netflix product recommendations
--Understanding human learning(brain,real AI).
What is Machine Learning
Arthur Samul(1959):Fileds of study that gives computers the ability to learn without being explicitly programmed.--机器在某领域中的自动学习能力
Tom Mitchell(1998):A computer program is said to learn from experience E with respect to some task T and some performace measure P,if its performace on T,as measured P,improves with experience E.--对于一个任务T,具有经验E,如果此时有P动作执行在T上,那么根据P的执行结果,可以提高经验E。即根据对任务T不同的动作P累积经验E。
两种算法:
--supervised learning(被动学习)
为程序给出了正确的经验,即根据先验的样本,计算出解析方式,程序根据解析方式给出结果并提高概率。
有两种类型:regression problem--回归问题,得出一个数值
classification problem--分类问题,答案是离散的值
--unsupervised learning(主动学习)
程序根据样本的特征进行分析,并自发计算出分类方式。
--两者的区别:前者给出分类,根据分类结果对新数据进行分类学习,给出答案;
后者是根据数据的特征对其进行分类;
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