标签：what algorithm Introduction answers Machine learning output data
1、What is machine learning
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Field of study that gives computers the ability to learn without being explicitly programmed
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A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E
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2、Supervised learning
- One example ：Housing price prediction
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It refers to the fact that we give the algorithm a data set in which the ''right answers'' were given. (also called a regression problem 回归问题... Regression-> continuous valued output )
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Just to produce more ''right answers''
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The other example : Breast cancer
- It refers to the fact that we give the algorithm to predict discrete set of output (Classification-> discrete valued output[0 or 1] 分类问题)
- A learning algorithm can deal with not two or three features, but an infinite number of features
3、Unsupervised learning
- We just tell the algorithm that here is a bunch of data ，but we don't know what is in this data，who is in what type and what the different types of this data . But the algorithm can automatically find the structure of this data and cluster the individuals into these types that we don't know in advance.(There is no "right answers" for machine)
- Application:
- A example: Cocktail party problem algorithm: [W,s, v]= svd((repmat(sum(x .* x, 1), size (x, 1), 1).* x) *x');
标签：what,algorithm,Introduction,answers,Machine,learning,output,data 来源： https://www.cnblogs.com/wangzheming35/p/14854543.html
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