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Feature selection for classification with class-separability strategy and data envelopment analysis [article]

Yishi Zhang, Chao Yang, Anrong Yang, Chan Xiong, Xingchi Zhou, Zigang Zhang
2015 arXiv   pre-print
In this paper, a novel feature selection method is presented, which is based on Class-Separability (CS) strategy and Data Envelopment Analysis (DEA).  ...  set for conditional dependence estimation in the next iteration, in such a way as to iteratively select features and get the final selected features.  ...  Acknowledgement The authors would like to thank the anonymous referees for their constructive comments which were very helpful in revising this paper.  ... 
arXiv:1405.1119v2 fatcat:p7weti4u6be7lhxl7e6zj7lp4q

An intelligent condition-based maintenance platform for rotating machinery

Van Tung Tran, Bo-Suk Yang
2012 Expert systems with applications  
This strategy commonly consists of sequent modules such as data acquisition, signal processing, feature extraction and feature selection, condition monitoring, etc.  ...  Expert Systems With Applications, 39 (3). pp. 29772988.  ...  Acknowledgments The authors gratefully acknowledge the support of Brain Korea 21 Project and The Vietnam National Foundation for Science and Technology Development (NAFOSTED) for this study.  ... 
doi:10.1016/j.eswa.2011.08.159 fatcat:cnfrwvzckjgmxfxhshydonci4u

Sound event classification based on Feature Integration, Recursive Feature Elimination and Structured Classification

Huy Dat Tran, Haizhou Li
2009 2009 IEEE International Conference on Acoustics, Speech and Signal Processing  
The RFESVM is combined with a structured classification designed for our task in surveillance and security applications.  ...  This paper proposes a novel system for sound event classification based on Feature Integration, Recursive Feature Elimination Support Vector Machine (RFESVM) and Structured Classification.  ...  One hour data is used to test and the remaining for training and system calibration.  ... 
doi:10.1109/icassp.2009.4959549 dblp:conf/icassp/DatL09 fatcat:6tjwsazynrflvk5e23vh3xa3om

fMRI Based Cerebral Instantaneous Parameters for Automatic Alzheimer's, Mild Cognitive Impairment and Healthy Subject Classification [article]

Esmaeil Seraj, Mehran Yazdi, Nastaran Shahparian
2019 arXiv   pre-print
To this end, after performing the region-of-interest (ROI) analysis on fMRI data, different features covering power, entropy and coherency aspects of data are derived from instantaneous phase and envelope  ...  A Student's t-test has been used to select the most relevant features from chosen sets. Finally, a K-NN classifier is used to distinguish between classes in a three-class categorization problem.  ...  Acknowledgments This research has been supported by the Cognitive Sciences and Technologies Council of Iran (COGC), under the grant number 2250.  ... 
arXiv:1904.07441v1 fatcat:ecs7ijhhonh23fauagvwtd7xyy

Discriminant Feature Distribution Analysis-Based Hybrid Feature Selection for Online Bearing Fault Diagnosis in Induction Motors

Rashedul Islam, Sheraz Ali Khan, Jong-myon Kim
2016 Journal of Sensors  
The hybrid feature selection employs a genetic algorithm- (GA-) based filter analysis to select optimal features and ak-NN average classification accuracy-based wrapper analysis approach that selects the  ...  Optimal feature distribution and feature selection are of paramount importance for reliable fault diagnosis in induction motors.  ...  With the help of the evaluation method, GA selects an optimal feature set in 10 iterations of filter-based analysis on randomly selected data from the analysis dataset and creates an optimal feature occurrence  ... 
doi:10.1155/2016/7145715 fatcat:b55ijziytvawvmwclab636zwru

Automatic classification of traffic noise

Manuel A. Sobreira‐Seoane, Alfonso Rodríguez Molares, José Luis Alba Castro
2008 Journal of the Acoustical Society of America  
As first approach, the aim of the job was to determine if the different classes (trucks, cars and motorbikes) could be separable using different time and frequency characteristics.  ...  The results shows that for some of the characteristics the signals are separable, so a continuous traffic noise signal could be processed to get the information of the number of heavy trucks, cars and  ...  TEC2006-13883-C04-02, under the project An-ClaS3 "Sound source separation for acoustic mea-surements´´.  ... 
doi:10.1121/1.2935583 fatcat:k555xjckrzfwhjgoje7qkd7epe

Facial Expression Recognition Using Two-Class Discriminant Features [chapter]

Marios Kyperountas, Ioannis Pitas
2009 Lecture Notes in Computer Science  
The selection of these sets of features is accomplished by making use of a class separability measure that is utilized in an iterative process.  ...  For each such task, a unique set of features is identified that is enhanced, in terms of its ability to help produce a proper separation between the two specific classes.  ...  During each run of this strategy, one specific image is selected as the test data, whereas the remaining images are used to train the classification system.  ... 
doi:10.1007/978-3-642-04391-8_12 fatcat:fc77vl7ap5cinbsxawops3iyme

Improving Movement Analysis in Physical Therapy Systems Based on Kinect Interaction

Alina-Delia Calin, Horia F. Pop, Rares Florin Boian
2017 HCI 2017  
(with up to 56% for HMM and 32% for DTW).  ...  We propose a method to improve gesture recognition accuracy and motion analysis, by extracting from the full body motion data recorded by the Kinect sensor three important features which are relevant to  ...  By applying the Envelope Feature (EF) in CDB and FDB, we obtained data that was correlated with the amplitude of the movement.  ... 
doi:10.14236/ewic/hci2017.87 dblp:conf/bcshci/CalinPB17 fatcat:v5at46f5b5bldfikziobgbb2zm

An Efficient Audio Classification Approach Based on Support Vector Machines

Lhoucine Bahatti, Omar Bouattane, My Elhoussine, Mohamed Hicham
2016 International Journal of Advanced Computer Science and Applications  
The enhancement done by this work is also lay on the proposal of an optimal features selection procedure which combines filter and wrapper strategies.  ...  Experimental results show the accuracy and efficiency of the adopted approach in the binary classification as well as in the multi-class classification.  ...  For this, we adopt an algorithm based on linear discrimination analysis (LDA) strategy, called Inertia Ratio Maximization with Feature Space Projection (IRMFSP) [6] [13] ].  ... 
doi:10.14569/ijacsa.2016.070530 fatcat:aadhjsjqfvg3dh5tmxplzbk36u

Rolling Element Bearing Fault Diagnosis In Rotating Machines Of Oil Extraction Rigs

Rodrigo Batista, Eduardo Mendel, Thomas Rauber, Flávio Varejão
2009 Zenodo  
Acknowledgment We would like to thank CNPq (Grant N o 620165/2006-5) and COPES-Petrobras for the financial support given to the research from which this work originated.  ...  We would also like to thank the reviewers for their very helpful comments.  ...  The envelope analysis provides the feature vector used in the subsequent classification steps.  ... 
doi:10.5281/zenodo.41653 fatcat:7axox6peb5ar3bm5lje4sfl4hm


Karima Amara Korba, Orcid.Org/0000-0003-1769-3782, Fayçal Arbaoui
2018 Figshare  
A better efficiency in terms of time and classification rate goes to the multi-class SVM compared to the ANN and the NFN.  ...  In the classification phase, the Multi-Class Support Vector Machine (SVM) was chosen.  ...  MULTI-CLASS SVM CLASSIFICATION The multi-class SVM is an algorithm for finding the nonlinear separating hyper plane modeled as a constraint optimization problem of a Multi labeled dataset.  ... 
doi:10.6084/m9.figshare.6264611 fatcat:k4e7xa6ubvf5pa3pvacicrw5ny

Active Power Oscillation Property Classification of Electric Power Systems Based on SVM

Ju Liu, Wei Yao, Jinyu Wen, Haibo He, Xueyang Zheng
2014 Journal of Applied Mathematics  
Twenty sampling points of the envelope curve are selected as the feature matrices to train and test the supporting vector machine (SVM).  ...  Distinction from each other of those two different kinds of power oscillations becomes a precondition for suppressing the oscillations with proper measures.  ...  Acknowledgment This work was supported by the National Natural Science Foundation of China (nos. 51177057 and 51228701).  ... 
doi:10.1155/2014/218647 fatcat:p6rwpa5ierhshp7sfaeh2ngzxm

Detection and diagnosis of bottle capping failures based on motor current signature analysis

Moslem Azamfar, Xiaodong Jia, Vibhor Pandhare, Jaskaran Singh, Hoseein Davari, Jay Lee
2019 Procedia Manufacturing  
A generic model has been developed and it was used to analyze idle capacity and to design strategies towards the maximization of organization's value.  ...  This paper presents and discusses a mathematical model for capacity management based on different costing models (ABC and TDABC).  ...  SVM is employed for multi-class classification.  ... 
doi:10.1016/j.promfg.2019.06.165 fatcat:43def5ontvbyjblg4lxstmemty

Learning From Examples in the Small Sample Case: Face Expression Recognition

G. Guo, C.R. Dyer
2005 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
A pairwise framework for feature selection, instead of using all classes simultaneously, is presented.  ...  A new technique based on linear programming for both feature selection and classifier training is introduced.  ...  Mangasarian and S. Wright for their help on the linear programming technique, and M. Lyons for providing the face expression database.  ... 
doi:10.1109/tsmcb.2005.846658 pmid:15971916 fatcat:tykbzdbz2zg47om4rjihkoh66u

Feature selection for fault level diagnosis of planetary gearboxes

Zhiliang Liu, Xiaomin Zhao, Ming J. Zuo, Hongbing Xu
2014 Advances in Data Analysis and Classification  
We then employ the proposed feature selection algorithm to determine fault-sensitive features and select them for fault level diagnosis of planetary gearboxes.  ...  We develop a feature selection algorithm accordingly using the proposed criterion together with sequential backward selection and a feature re-ranking mechanism.  ...  Then we propose the criterion for class separability and the corresponding feature selection algorithm.  ... 
doi:10.1007/s11634-014-0168-4 fatcat:habl3iwn5vf6pgduh2auq2unl4
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