AU2002230050A1 - Feature selection for neural networks - Google Patents

Feature selection for neural networks

Info

Publication number
AU2002230050A1
AU2002230050A1 AU2002230050A AU2002230050A AU2002230050A1 AU 2002230050 A1 AU2002230050 A1 AU 2002230050A1 AU 2002230050 A AU2002230050 A AU 2002230050A AU 2002230050 A AU2002230050 A AU 2002230050A AU 2002230050 A1 AU2002230050 A1 AU 2002230050A1
Authority
AU
Australia
Prior art keywords
neural networks
feature selection
selection
feature
neural
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
AU2002230050A
Inventor
John Carney
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
PREDICTION DYNAMICS Ltd
Original Assignee
PREDICTION DYNAMICS Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by PREDICTION DYNAMICS Ltd filed Critical PREDICTION DYNAMICS Ltd
Publication of AU2002230050A1 publication Critical patent/AU2002230050A1/en
Abandoned legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/211—Selection of the most significant subset of features
    • G06F18/2115—Selection of the most significant subset of features by evaluating different subsets according to an optimisation criterion, e.g. class separability, forward selection or backward elimination

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Artificial Intelligence (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Computing Systems (AREA)
  • Software Systems (AREA)
  • Molecular Biology (AREA)
  • Computational Linguistics (AREA)
  • Biophysics (AREA)
  • Biomedical Technology (AREA)
  • Mathematical Physics (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Biology (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Image Analysis (AREA)
AU2002230050A 2001-01-31 2002-01-31 Feature selection for neural networks Abandoned AU2002230050A1 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
IE010076 2001-01-31
IE20010076 2001-01-31
PCT/IE2002/000012 WO2002061678A2 (en) 2001-01-31 2002-01-31 Feature selection for neural networks

Publications (1)

Publication Number Publication Date
AU2002230050A1 true AU2002230050A1 (en) 2002-08-12

Family

ID=11042724

Family Applications (1)

Application Number Title Priority Date Filing Date
AU2002230050A Abandoned AU2002230050A1 (en) 2001-01-31 2002-01-31 Feature selection for neural networks

Country Status (4)

Country Link
EP (1) EP1405263A2 (en)
AU (1) AU2002230050A1 (en)
IE (1) IES20020061A2 (en)
WO (1) WO2002061678A2 (en)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN100367300C (en) * 2006-07-07 2008-02-06 华中科技大学 Characteristic selecting method based on artificial nerve network
FI20070159A0 (en) 2007-02-23 2007-02-23 Teknillinen Korkeakoulu Procedure for integration of information, choice and learning of representation
CN107480686B (en) * 2016-06-08 2021-03-30 阿里巴巴集团控股有限公司 Method and device for screening machine learning characteristics
EP3562162A1 (en) * 2018-04-27 2019-10-30 InterDigital VC Holdings, Inc. Method and apparatus for video encoding and decoding based on neural network implementation of cabac
CN109934255B (en) * 2019-01-22 2023-05-30 小黄狗环保科技有限公司 Model fusion method suitable for classification and identification of delivered objects of beverage bottle recycling machine
CN114268625B (en) * 2020-09-14 2024-01-02 腾讯科技（深圳）有限公司 Feature selection method, device, equipment and storage medium

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5359699A (en) * 1991-12-02 1994-10-25 General Electric Company Method for using a feed forward neural network to perform classification with highly biased data
EP0696372A1 (en) * 1993-04-30 1996-02-14 Pavilion Technologies Inc. Method and apparatus for determining the sensitivity of inputs to a neural network on output parameters

Also Published As

Publication number Publication date
IE20020062A1 (en) 2002-08-07
EP1405263A2 (en) 2004-04-07
IES20020061A2 (en) 2002-08-07
WO2002061678A2 (en) 2002-08-08
WO2002061678A3 (en) 2004-01-22

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Legal Events

Date Code Title Description
MK6 Application lapsed section 142(2)(f)/reg. 8.3(3) - pct applic. not entering national phase