Linear classifier
Upcoming SlideShare
Loading in...5
×
 

Linear classifier

on

  • 1,251 views

A practical overview of linear classifier, including perceptron, SVM, structured perceptron and CRF. Some materials are copied from other slides.

A practical overview of linear classifier, including perceptron, SVM, structured perceptron and CRF. Some materials are copied from other slides.

Statistics

Views

Total Views
1,251
Views on SlideShare
1,251
Embed Views
0

Actions

Likes
0
Downloads
14
Comments
0

0 Embeds 0

No embeds

Accessibility

Upload Details

Uploaded via as Adobe PDF

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Linear classifier Linear classifier Presentation Transcript

  • A  Praccal  Overview  of  Linear   Classifier
  • Discriminave/Generave  Pair
  • Quesons•  Advantages/disadvantages  of  generave/ discriminave  model?  •  Can  we  combine  generave  and  discriminave   model?
  • Outline•  Perceptron  •  Margin  •  Kernel  •  Structure  •  Online  •  Ensemble
  • Generic  Perceptron
  • Margin
  • Max  Margin  Helps
  • Percptron  VS  SVM
  • Theory•  Theorecal  jusficaon:   –  Large  margin  implies  small  VC  dimension  •  Stascal  Learning  Theory  (SLT)   –  VC-­‐dimension  (Vapnik-­‐Chervonenkis)  •  Probably  Approximately  Correct  (PAC)  Theory  
  • Parameter  Esmaon  •  SMO  algorithm  •  Online  algorithm
  • Classifier  Comparison  on  Senment  Classificaon Accuracy
  • Quesons•  What  if  not  linear  separable?  •  Can  SVM  be  used  when  some  data  do  not   have  labels?
  • Kernel
  • Why  Linear  Classifier•  Simple  •  Applicable  •  Fast
  • Kernel:  Nonlinear  -­‐>  Linear  
  • Kernel  SVM
  • Quesons•  What  is  the  best  kernel?  •  Can  we  use  mulple  kernels?  •  kernels  for  NLP?
  • Structure
  • Feature  Funcons
  • Applicaon1:  POS  Tagging
  • Applicaon2:  NP  Chunking
  • Quesons•  Relaonship  to  CRF?  •  Structured  SVM?  •  Maximum  Margin  Markov  Network?
  • Ensemble  Perceptron•  Many  classifiers  are  beXer  than  one  •  Vong  perceptron  •  Average  perceptron
  • Online  Learning•  Batch  •  Online  •  MiniBatch
  • ImplementaonsAlgorithm Implemena/onPerceptron Sklearn(Python),  Weka(Java)SVM LibSVM,  LibLinear(Linear  kernel)Logisc  regression/Maximum  Entropy LibLinearCRF CRF++,  CRFSuiteNaïve  Bayes Sklean,  Weka
  • Perceptron  and  Beyond Kernel Online Kernel  SVM Online  SVM Kernel  perceptron Online  CRF PerceptronMargin Vong  perceptron Linear  SVM Ensemble Averaged  perceptron Margin  perceptron Structured  Perceptron Boosng Structured  SVM CRF M3N Structure
  • Examples•  hXp://www.mathworks.com/matlabcentral/ fileexchange/28302-­‐svm-­‐demo  •  hXp://www.eee.metu.edu.tr/~alatan/ Courses/Demo/AppletSVM.html