WO2014195782A3 - Differential evolution-based feature selection - Google Patents

Differential evolution-based feature selection Download PDF

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Publication number
WO2014195782A3
WO2014195782A3 PCT/IB2014/000939 IB2014000939W WO2014195782A3 WO 2014195782 A3 WO2014195782 A3 WO 2014195782A3 IB 2014000939 W IB2014000939 W IB 2014000939W WO 2014195782 A3 WO2014195782 A3 WO 2014195782A3
Authority
WO
WIPO (PCT)
Prior art keywords
variation factor
class variation
differential evolution
feature selection
amongst
Prior art date
Application number
PCT/IB2014/000939
Other languages
French (fr)
Other versions
WO2014195782A2 (en
Inventor
Kingshuk CHAKRAVARTY
Diptesh DAS
Aniruddha Sinha
Amit Konar
Original Assignee
Tata Consultancy Services Limited
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 Tata Consultancy Services Limited filed Critical Tata Consultancy Services Limited
Publication of WO2014195782A2 publication Critical patent/WO2014195782A2/en
Publication of WO2014195782A3 publication Critical patent/WO2014195782A3/en

Links

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/369—Electroencephalography [EEG]
    • 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
    • G06F18/2111—Selection of the most significant subset of features by using evolutionary computational techniques, e.g. genetic algorithms
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/08—Feature extraction
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

The subject matter discloses systems and methods for selection of an optimum feature subset. According to the present subject matter, the system (102) implements the described method, where the method includes obtaining a plurality of features extracted from data sets associated with objects representing multiple classes, computing an intra-class variation factor and an inter-class variation factor for multiple feature subsets, from amongst the plurality of features, and identifying an optimum feature subset, from amongst the multiple feature subsets, based on minimization of the intra-class variation factor and maximization of the inter-class variation factor using differential evolution.
PCT/IB2014/000939 2013-06-03 2014-06-03 Differential evolution-based feature selection WO2014195782A2 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
IN1938/MUM/2013 2013-06-03
IN1938MU2013 IN2013MU01938A (en) 2013-06-03 2014-06-03

Publications (2)

Publication Number Publication Date
WO2014195782A2 WO2014195782A2 (en) 2014-12-11
WO2014195782A3 true WO2014195782A3 (en) 2015-02-05

Family

ID=52008655

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/IB2014/000939 WO2014195782A2 (en) 2013-06-03 2014-06-03 Differential evolution-based feature selection

Country Status (2)

Country Link
IN (1) IN2013MU01938A (en)
WO (1) WO2014195782A2 (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105184803A (en) * 2015-09-30 2015-12-23 西安电子科技大学 Attitude measurement method and device

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105137717B (en) * 2015-08-05 2018-08-24 哈尔滨工业大学 The mechanical parameter flexible measurement method of mask aligner mask platform micropositioner based on Compact Differential Evolution algorithms
US10558933B2 (en) 2016-03-30 2020-02-11 International Business Machines Corporation Merging feature subsets using graphical representation
CN108573338A (en) * 2018-03-14 2018-09-25 中山大学 A kind of distributed differential evolution algorithm and device based on MPI
CN109636487B (en) * 2019-01-14 2023-09-29 平安科技（深圳）有限公司 Advertisement pushing method, server, computer device and storage medium
CN109885710B (en) * 2019-01-14 2022-03-18 平安科技（深圳）有限公司 User image depicting method based on differential evolution algorithm and server
CN111553530B (en) * 2020-04-27 2022-08-02 华侨大学 Inter-city network car booking and packing travel capacity prediction and travel recommendation method and system

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040071363A1 (en) * 1998-03-13 2004-04-15 Kouri Donald J. Methods for performing DAF data filtering and padding
US20080101705A1 (en) * 2006-10-31 2008-05-01 Motorola, Inc. System for pattern recognition with q-metrics
US20100094155A1 (en) * 2005-10-31 2010-04-15 New York University System and Method for Prediction of Cognitive Decline
US20100111396A1 (en) * 2008-11-06 2010-05-06 Los Alamos National Security Object and spatial level quantitative image analysis
US20100158334A1 (en) * 2004-07-01 2010-06-24 Johanne Martel-Pelletier Non-invasive joint evaluation

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040071363A1 (en) * 1998-03-13 2004-04-15 Kouri Donald J. Methods for performing DAF data filtering and padding
US20100158334A1 (en) * 2004-07-01 2010-06-24 Johanne Martel-Pelletier Non-invasive joint evaluation
US20100094155A1 (en) * 2005-10-31 2010-04-15 New York University System and Method for Prediction of Cognitive Decline
US20080101705A1 (en) * 2006-10-31 2008-05-01 Motorola, Inc. System for pattern recognition with q-metrics
US20100111396A1 (en) * 2008-11-06 2010-05-06 Los Alamos National Security Object and spatial level quantitative image analysis

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105184803A (en) * 2015-09-30 2015-12-23 西安电子科技大学 Attitude measurement method and device

Also Published As

Publication number Publication date
WO2014195782A2 (en) 2014-12-11
IN2013MU01938A (en) 2015-05-29

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