Journal of Computer and Communications

Journal of Computer and Communications

ISSN Print: 2327-5219
ISSN Online: 2327-5227
www.scirp.org/journal/jcc
E-mail: jcc@scirp.org
"Enhanced Classification Accuracy for Cardiotocogram Data with Ensemble Feature Selection and Classifier Ensemble"
written by Tipawan Silwattananusarn, Wanida Kanarkard, Kulthida Tuamsuk,
published by Journal of Computer and Communications, Vol.4 No.4, 2016
has been cited by the following article(s):
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[1] Machine Learning Techniques for Identifying Fetal Risk During Pregnancy
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[2] Association Rule Mining Based on Ethnic Groups and Classification using Super Learning 1
Applied Smart Health Care Informatics …, 2022
[3] Health Monitoring Methods in Heart Diseases Based on Data Mining Approach: A Directional Review
Prognostic Models in …, 2022
[4] Classification of Cardiotocography based on Apriori algorithm and multi-model ensemble classifier
Frontiers in Cell and Developmental Biology, 2022
[5] Healthcare Analytics Using Machine Learning
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[6] Classification of Cardiotocography Data for Fetal Health Using Feature Selection Techniques
Computer Science On-line Conference, 2021
[7] Analyzing uncertainty in cardiotocogram data for the prediction of fetal risks based on machine learning techniques using rough set
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[8] Improving performance with hybrid feature selection and ensemble machine learning techniques for code smell detection
Science of Computer Programming, 2021
[9] Towards Making More Reliable Cardiotocogram Data Prediction with Limited Expert Knowledge: Exploiting Unlabeled Data with Semi-supervised Boosting Method
… Conference on Data Mining and Big …, 2021
[10] Classification and Feature Selection Approaches for Cardiotocography by Machine Learning Techniques
2020
[11] Fetal Health Status Classification Using MOGA-CD Based Feature Selection Approach
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[12] Extracting Useful Information and Building Predictive Models from Medical and Health-care Data Using Machine Learning Techniques
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[13] Exploring Fetal Health Status Using an Association Based Classification Approach
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[14] LITERATURE SURVEY ON MACHINE LEARNING BASED TECHNIQUES IN MEDICAL DATA ANALYSIS
2019
[15] Performance Assessment of Different Machine Learning Algorithms for Medical Decision Support Systems
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[16] A Novel LtR and RtL Framework for Subset Feature Selection (Reduction) for Improving the Classification Accuracy
2019
[17] Enhancing the Performance of Classification Using Super Learning
2019
[18] An Ensemble Feature Selection Method to Detect Web Spam
2018
[19] Analiza metod przetwarzania informacji ruchu sieciowego
2018
[20] A Feature Selection Approach for Enhancing the Cardiotocography Classification Performance
International Journal of Engineering and Techniques, 2018
[21] A hybrid gene selection method for microarray recognition
Biocybernetics and Biomedical Engineering, 2018
[22] A Novel M-Cluster of Feature Selection Approach Based on Symmetrical Uncertainty for Increasing Classification Accuracy of Medical Datasets.
2017
[23] Ensemble Features Selection Algorithm by Considering Features Ranking Priority
Recent Advances in Information and Communication Technology 2017, 2017
[24] A Novel M-Cluster of Feature Selection Approach Based on Symmetrical Uncertainty for Increasing Classification Accuracy of Medical Datasets
2017
[25] Predicting Optimal Trading Actions Using a Genetic Algorithm and Ensemble Method
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[26] Application of Machine Learning Techniques to classify Fetal Hypoxia
2016
[27] COMPARATIVE ANALYSIS OF DIMENSION REDUCTION AND CLASSIFICATION USING CARDIOTOCOGRAPHY DATA
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