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机器学习基石 - The Learning Problem
阅读量:4091 次
发布时间:2019-05-25

本文共 2323 字,大约阅读时间需要 7 分钟。

,副教授 (Associate Professor),资讯工程学系 (Computer Science and Information Engineering)

The Learning Problem

What Is Machine Learning

  • observation → learning → skill
  • data → ML → skill
  • skill ↔ improve some performance measure
  • machine learning: improve some performance measure with experience computed from data
  • ML: an alternative route to build complicated system
    • some use scenarios
      scenarios

Key Essence of Machine Learning

  • 具有潜在的模式
  • 不能简单的编写出来程序
  • 大量的数据

key essence

Examples

example

Applications of Machine Learning

  • Food, Housing, Transport. Clothes. Education, Entertainment
  • Learn our performances
  • Examples
    example-2

Components of Machine Learning

  • input: xX x ∈ X
  • output: yY y ∈ Y
  • unknown pattern to be learnt (target function): f:XY f : X → Y
  • data (training examples): D={
    (x1,y1),(x2,y2),...,(xN,yN)}
    D = { ( x 1 , y 1 ) , ( x 2 , y 2 ) , . . . , ( x N , y N ) }
  • hypothesis (skill with hopefully good performance): g:XY g : X → Y
  • {
    (xn,yn)} from fMLg
    { ( x n , y n ) }   f r o m   f → M L → g
    , f f 是真正的模式,但学不到,
    g
    是学习之后给出的模式
  • 学习过程
    • f f is unknown (no programmable definition)
    • 希望
      g
      f f 尽量接近(假设函数和目标函数)
    • assume
      g
      H
      =
      {
      h
      k
      }
      , hypothesis set H H can contain good or bad hypotheses
    • learning algorithm A A to pick the ‘best’ one as g g
  • machine learning: use data to compute hypothesis
    g
    that approximates target f f

Machine Learning and Other Fields

Machine Learning and Data Mining

  • 资料勘探即数据挖掘 (Data Mining)

    use huge data to find property that is interesting

  • if ‘interesting property’ same as ‘hypothesis that approximate target’ —— ML = DM

  • if ‘interesting property’ related to ‘hypothesis that approximate target’ —— DM can help ML, and vice versa (but not always)

  • traditional DM also focuses on efficient computation in large database

Machine Learning and Artificial Intelligence

  • 人工智能 (Artificial Intelligence)

    compute something that shows intelligent behavior

  • ML is one possible route to realize AI (机器学习是实现人工智能的一种方法)

  • g
    f
    is something that shows intelligent behavior

Machine Learning and Statistics

  • 统计学 (Statistics)

    use data to make inference(推断) about an unknown process

  • g g is an inference outcome while

    f
    is something unknown

  • statistics can be used to achieve ML (统计是实现机器学习的一种方法)

  • traditional statistics also focus on provable results with math assumptions (侧重数学上的推论), and care less about computation

  • In statistics, there are many useful tools for ML

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