Feature selection of stabilometric parameters based on principal component analysis

Medical & Biological Engineering & Computing ◽

10.1007/bf02351013 ◽

2004 ◽

Vol 42 (1) ◽

pp. 71-79 ◽

Author(s):

L. Rocchi ◽

L. Chiari ◽

A. Cappello

Keyword(s):

Principal Component Analysis ◽

Feature Selection ◽

Principal Component ◽

Component Analysis ◽

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Modified Principal Component Analysis (MPCA) for feature selection of hyperspectral imagery

IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477) ◽

10.1109/igarss.2003.1295268 ◽

2004 ◽

Author(s):

Cheng Wang ◽

M. Menenti ◽

Zhao-Liang Li

Keyword(s):

Principal Component Analysis ◽

Feature Selection ◽

Hyperspectral Imagery ◽

Principal Component ◽

Component Analysis ◽

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Sparse principal component analysis for feature selection of multiple physiological signals from flight task

2015 15th International Conference on Control, Automation and Systems (ICCAS) ◽

10.1109/iccas.2015.7364994 ◽

2015 ◽

Author(s):

Dongbo Bai ◽

Wei Liming ◽

Wei Chan ◽

Qi Wu ◽

Dan Huang ◽

...

Keyword(s):

Principal Component Analysis ◽

Feature Selection ◽

Principal Component ◽

Component Analysis ◽

Physiological Signals ◽

Sparse Principal Component Analysis ◽

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Feature selection of weather data with interval principal component analysis

2016 International Conference on System Science and Engineering (ICSSE) ◽

10.1109/icsse.2016.7551600 ◽

2016 ◽

Author(s):

Chong-Cheng He ◽

Jin-Tsong Jeng

Keyword(s):

Principal Component Analysis ◽

Feature Selection ◽

Principal Component ◽

Component Analysis ◽

Weather Data ◽

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Feature Selection of Oral Cyst and Tumor Images Using Principal Component Analysis

2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT) ◽

10.1109/eiconcit.2018.8878641 ◽

2018 ◽

Author(s):

Syahrul Mubarak ◽

Herdianti Darwis ◽

Fitriyani Umar ◽

Lutfi Budi Ilmawan ◽

Siska Anraeni ◽

...

Keyword(s):

Principal Component Analysis ◽

Feature Selection ◽

Principal Component ◽

Component Analysis ◽

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Feature selection of postural summary statistic scores based on principal component analysis in Parkinson’s disease

Modelling in Medicine and Biology VI ◽

10.2495/bio050511 ◽

2005 ◽

Author(s):

L. Rocchi ◽

L. Chiari ◽

A. Cappello ◽

F. B. Horak

Keyword(s):

Parkinson’S Disease ◽

Principal Component Analysis ◽

Parkinson's Disease ◽

Feature Selection ◽

Principal Component ◽

Component Analysis ◽

Summary Statistic ◽

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Feature selection of manifold learning using principal component analysis in brain MR image

2015 International Conference on Informatics, Electronics & Vision (ICIEV) ◽

10.1109/iciev.2015.7334065 ◽

2015 ◽

Author(s):

Saadia Binte Alam ◽

Ryosuke Nakano ◽

Syoji Kobashi ◽

Naotake Kamiura

Keyword(s):

Principal Component Analysis ◽

Feature Selection ◽

Manifold Learning ◽

Principal Component ◽

Component Analysis ◽

Mr Image ◽

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Feature selection of breast cancer based on Principal Component Analysis

2010 6th International Colloquium on Signal Processing & its Applications ◽

10.1109/cspa.2010.5545298 ◽

2010 ◽

Author(s):

Hasmarina Hasan ◽

Nooritawati Md Tahir

Keyword(s):

Breast Cancer ◽

Principal Component Analysis ◽

Feature Selection ◽

Principal Component ◽

Component Analysis ◽

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Studies on the selection of cutting parameters of Ti-6Al-4V alloy turning operation using principal component analysis

Materials Today Proceedings ◽

10.1016/j.matpr.2021.03.593 ◽

2021 ◽

Author(s):

Geetika k. Salwan ◽

Rayapati Subbarao

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Cutting Parameters ◽

Component Analysis ◽

Turning Operation ◽

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Feature Selection for Classification using Principal Component Analysis and Information Gain

Expert Systems with Applications ◽

10.1016/j.eswa.2021.114765 ◽

2021 ◽

Vol 174 ◽

pp. 114765 ◽

Author(s):

Erick Odhiambo Omuya ◽

George Onyango Okeyo ◽

Michael Waema Kimwele

Keyword(s):

Principal Component Analysis ◽

Feature Selection ◽

Information Gain ◽

Principal Component ◽

Component Analysis ◽

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Multiclass classification of leukemia cancer data using Fuzzy Support Vector Machine (FSVM) with feature selection using Principal Component Analysis (PCA)

Journal of Physics Conference Series ◽

10.1088/1742-6596/1725/1/012012 ◽

2021 ◽

Vol 1725 ◽

pp. 012012

Author(s):

I R Fauzi ◽

Z Rustam ◽

A Wibowo

Keyword(s):

Principal Component Analysis ◽

Support Vector Machine ◽

Feature Selection ◽

Principal Component ◽

Component Analysis ◽

Multiclass Classification ◽

Support Vector ◽

Fuzzy Support Vector Machine ◽

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