An intelligent hybrid approach for hepatitis disease diagnosis: Combining enhanced k-means clustering and improved ensemble learning
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[1] David W. Opitz,et al. An Empirical Evaluation of Bagging and Boosting , 1997, AAAI/IAAI.
[2] Olgierd Unold,et al. Mining fuzzy rules using an Artificial Immune System with fuzzy partition learning , 2011, Appl. Soft Comput..
[3] Oscar Camacho Nieto,et al. An associative memory approach to medical decision support systems , 2012, Comput. Methods Programs Biomed..
[4] Kemal Polat,et al. Medical decision support system based on artificial immune recognition immune system (AIRS), fuzzy weighted pre-processing and feature selection , 2007, Expert Syst. Appl..
[5] J. Ross Quinlan,et al. Bagging, Boosting, and C4.5 , 1996, AAAI/IAAI, Vol. 1.
[6] Jian Jhen Chen,et al. K-means clustering versus validation measures: a data-distribution perspective. , 2009, IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society.
[7] Aditya Khamparia,et al. Seasonal Crops Disease Prediction and Classification Using Deep Convolutional Encoder Network , 2019, Circuits, Systems, and Signal Processing.
[8] Eric Bauer,et al. An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants , 1999, Machine Learning.
[9] Lale Özbakir,et al. Cost-sensitive meta-learning classifiers: MEPAR-miner and DIFACONN-miner , 2016, Knowl. Based Syst..
[10] Ling Zhen,et al. Novel Grouping Method-based support vector machine plus for structured data , 2016, Neurocomputing.
[11] Kemal Polat,et al. A novel hybrid intelligent method based on C4.5 decision tree classifier and one-against-all approach for multi-class classification problems , 2009, Expert Syst. Appl..
[12] Kay Chen Tan,et al. A hybrid evolutionary algorithm for attribute selection in data mining , 2009, Expert Syst. Appl..
[13] Robert E. Schapire,et al. The Boosting Approach to Machine Learning An Overview , 2003 .
[14] W. Dich,et al. Minimal distance neural methods , 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).
[15] Jamil Ahmad,et al. Diagnosis of liver disease induced by hepatitis virus using Artificial Neural Networks , 2011, 2011 IEEE 14th International Multitopic Conference.
[16] Massimo Melucci,et al. Binary Classification Model Inspired from Quantum Detection Theory , 2018, ICTIR.
[17] Wlodzislaw Duch,et al. Optimization of logical rules derived by neural procedures , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).
[18] Aditya Khamparia,et al. Sound Classification Using Convolutional Neural Network and Tensor Deep Stacking Network , 2019, IEEE Access.
[19] Esin Dogantekin,et al. A new intelligent hepatitis diagnosis system: PCA-LSSVM , 2011, Expert Syst. Appl..
[20] M. Serdar Bascil,et al. A Study on Hepatitis Disease Diagnosis Using Multilayer Neural Network with Levenberg Marquardt Training Algorithm , 2011, Journal of Medical Systems.
[21] U. Rajendra Acharya,et al. A novel machine learning approach for early detection of hepatocellular carcinoma patients , 2019, Cognitive Systems Research.
[22] Massimo Melucci,et al. Towards a Quantum-Inspired Framework for Binary Classification , 2018, CIKM.
[23] Kemal Polat,et al. Hepatitis disease diagnosis using a new hybrid system based on feature selection (FS) and artificial immune recognition system with fuzzy resource allocation , 2006, Digit. Signal Process..
[24] Aditya Khamparia,et al. A novel deep learning-based multi-model ensemble method for the prediction of neuromuscular disorders , 2018, Neural Computing and Applications.
[25] Novruz Allahverdi,et al. Extracting rules for classification problems: AIS based approach , 2009, Expert Syst. Appl..
[26] Ajith Abraham,et al. A self adaptive harmony search based functional link higher order ANN for non-linear data classification , 2016, Neurocomputing.
[27] Antonio J. Serrano,et al. A framework for modelling the biomechanical behaviour of the human liver during breathing in real time using machine learning , 2017, Expert Syst. Appl..
[28] Jing Yuan,et al. Assessment of liver fibrosis in chronic hepatitis B via multimodal data , 2017, Neurocomputing.
[29] Esin Dogantekin,et al. Automatic hepatitis diagnosis system based on Linear Discriminant Analysis and Adaptive Network based on Fuzzy Inference System , 2009, Expert Syst. Appl..
[30] Jafar Habibi,et al. Disease Diagnosis with a hybrid method SVR using NSGA-II , 2014, Neurocomputing.
[31] Liu Jiang Hua,et al. The Research of Emotional Cognition Model which Based On Bayesian Network within Intelligent Tutoring System , 2009, 2009 International Conference on Computational Intelligence and Natural Computing.
[32] Yoichi Hayashi,et al. Accuracy of rule extraction using a recursive-rule extraction algorithm with continuous attributes combined with a sampling selection technique for the diagnosis of liver disease , 2018 .
[33] Robert E. Schapire,et al. Explaining AdaBoost , 2013, Empirical Inference.
[34] N. Arunkumar,et al. Optimized cuttlefish algorithm for diagnosis of Parkinson’s disease , 2018, Cognitive Systems Research.
[35] Arun Sharma,et al. Diagnosis of Parkinson’s disease using modified grey wolf optimization , 2019, Cognitive Systems Research.
[36] Chieh-Chen Wu,et al. Prediction of fatty liver disease using machine learning algorithms , 2019, Comput. Methods Programs Biomed..
[37] Douglas Steinley,et al. K-means clustering: a half-century synthesis. , 2006, The British journal of mathematical and statistical psychology.
[38] Kourosh Mozafari,et al. Hepatitis disease diagnosis using a novel hybrid method based on support vector machine and simulated annealing (SVM-SA) , 2012, Comput. Methods Programs Biomed..
[39] Tom J. Moir. Automatic variance control and variance estimation loops , 2001 .
[40] Massimo Melucci,et al. Binary Classifier Inspired by Quantum Theory , 2019, AAAI.
[41] D. Opitz,et al. Popular Ensemble Methods: An Empirical Study , 1999, J. Artif. Intell. Res..
[42] Tulay Yildirim,et al. Artificial neural networks for diagnosis of hepatitis disease , 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..
[43] Mohammed Erritali,et al. A comparative study of decision tree ID3 and C4.5 , 2014 .
[44] Panayiotis E. Pintelas,et al. Combining Bagging and Boosting , 2007 .