EvaGoNet: An integrated network of variational autoencoder and Wasserstein generative adversarial network with gradient penalty for binary classification tasks
Feature engineering is an effective method for solving classification problems. Many existing feature engineering studies have focused on image or video data and not on structured data. This study proposes EvaGoNet, which refines the decoder module of the Gaussian mixture variational autoencoder usi...
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| Vydáno v: | Information sciences Ročník 629; s. 109 - 122 |
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| Hlavní autoři: | , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Inc
01.06.2023
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| ISSN: | 0020-0255, 1872-6291 |
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| Abstract | Feature engineering is an effective method for solving classification problems. Many existing feature engineering studies have focused on image or video data and not on structured data. This study proposes EvaGoNet, which refines the decoder module of the Gaussian mixture variational autoencoder using the Wasserstein generative adversarial network with gradient penalty (WGANgp) and embeds the top-ranked original features to update the latent features based on their discriminative powers. Comprehensive experiments show that EvaGoNet-encoded features outperform existing classifiers on 12 benchmark datasets, particularly on the small, imbalanced datasets col (accuracy = 0.8581), spe (accuracy = 1.0000), and leu (accuracy = 0.8021). EvaGoNet-engineered features improve binary classification task outcomes on six high-dimensional, imbalanced bioOMIC datasets. EvaGoNet achieves a medium-ranked training speed among the compared algorithms and considerably fast prediction speeds in the predictions of the testing samples. Therefore, EvaGoNet can be a candidate feature engineering framework for many practical applications that require one training procedure and many prediction tasks of the testing samples. EvaGoNet is implemented in Python TensorFlow and is available at https://healthinformaticslab.org/supp/resources.php. |
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| AbstractList | Feature engineering is an effective method for solving classification problems. Many existing feature engineering studies have focused on image or video data and not on structured data. This study proposes EvaGoNet, which refines the decoder module of the Gaussian mixture variational autoencoder using the Wasserstein generative adversarial network with gradient penalty (WGANgp) and embeds the top-ranked original features to update the latent features based on their discriminative powers. Comprehensive experiments show that EvaGoNet-encoded features outperform existing classifiers on 12 benchmark datasets, particularly on the small, imbalanced datasets col (accuracy = 0.8581), spe (accuracy = 1.0000), and leu (accuracy = 0.8021). EvaGoNet-engineered features improve binary classification task outcomes on six high-dimensional, imbalanced bioOMIC datasets. EvaGoNet achieves a medium-ranked training speed among the compared algorithms and considerably fast prediction speeds in the predictions of the testing samples. Therefore, EvaGoNet can be a candidate feature engineering framework for many practical applications that require one training procedure and many prediction tasks of the testing samples. EvaGoNet is implemented in Python TensorFlow and is available at https://healthinformaticslab.org/supp/resources.php. |
| Author | Luo, Changfan Liu, Yuchen Duan, Meiyu Huang, Lan Hu, Jianzheng Shao, Yongkang Yuan, Jiawei Zhou, Fengfeng Xu, Yiping Wang, Zihan |
| Author_xml | – sequence: 1 givenname: Changfan surname: Luo fullname: Luo, Changfan organization: College of Software, Jilin University, Changchun, Jilin 130012, China – sequence: 2 givenname: Yiping surname: Xu fullname: Xu, Yiping organization: College of Software, Jilin University, Changchun, Jilin 130012, China – sequence: 3 givenname: Yongkang surname: Shao fullname: Shao, Yongkang organization: College of Software, Jilin University, Changchun, Jilin 130012, China – sequence: 4 givenname: Zihan orcidid: 0000-0003-1056-6326 surname: Wang fullname: Wang, Zihan organization: School of Life Science, Jilin University, Changchun, Jilin 130012, China – sequence: 5 givenname: Jianzheng orcidid: 0000-0003-3342-0688 surname: Hu fullname: Hu, Jianzheng organization: College of Computer Science and Technology, Jilin University, Changchun, Jilin 130012, China – sequence: 6 givenname: Jiawei surname: Yuan fullname: Yuan, Jiawei organization: School of Life Science, Jilin University, Changchun, Jilin 130012, China – sequence: 7 givenname: Yuchen surname: Liu fullname: Liu, Yuchen organization: School of Life Science, Jilin University, Changchun, Jilin 130012, China – sequence: 8 givenname: Meiyu orcidid: 0000-0001-7171-2695 surname: Duan fullname: Duan, Meiyu email: dmy235813@163.com organization: Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130012, China – sequence: 9 givenname: Lan surname: Huang fullname: Huang, Lan organization: Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130012, China – sequence: 10 givenname: Fengfeng orcidid: 0000-0002-8108-6007 surname: Zhou fullname: Zhou, Fengfeng email: ffzhou@jlu.edu.cn organization: Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130012, China |
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| Cites_doi | 10.1109/TKDE.2005.182 10.1016/j.asoc.2019.105854 10.1016/j.knosys.2020.105806 10.1016/j.asoc.2019.04.039 10.3389/fnagi.2017.00329 10.1016/j.ins.2022.05.025 10.1016/j.eswa.2021.116288 10.1007/978-981-15-6876-3_16 10.1016/j.asoc.2020.106826 10.1016/j.aap.2020.105950 10.1080/01621459.2017.1285773 10.1016/j.asoc.2020.107003 10.1016/j.neuroimage.2017.09.001 10.1007/s11042-018-5878-8 10.1038/nature13385 10.1016/S0950-7051(01)00103-4 10.1073/pnas.96.12.6745 10.1609/aaai.v34i04.6146 10.1007/s00521-018-3677-9 10.1016/j.media.2021.102099 10.1126/science.286.5439.531 10.1007/s11831-020-09452-y 10.1007/s12293-015-0173-y 10.1016/j.ins.2021.05.079 10.1007/s00500-020-05453-y 10.1016/j.ins.2021.11.063 10.1016/j.cell.2014.09.050 10.1007/s10115-017-1059-8 10.1016/j.ins.2022.10.068 10.1177/0272989X15618658 10.1016/j.asoc.2021.107173 10.1016/j.ins.2021.03.007 10.1016/j.ins.2022.02.049 10.1016/j.ins.2021.09.036 10.1093/bioinformatics/btab109 10.1155/2020/1459107 10.1016/j.ins.2019.07.065 10.1016/j.asoc.2019.105489 10.1016/j.ins.2022.08.059 10.1016/j.ins.2022.04.058 10.1109/TNN.2010.2094624 10.1016/j.ins.2019.05.023 |
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| Keywords | WGANgp VAE Gaussian mixture VAE Feature engineering bioOMIC data EvaGoNet |
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| References | Zhu, Fang (b0250) 2016; 36 D.P. Kingma, M. Welling, Auto-encoding variational bayes, arXiv preprint arXiv:1312.6114, (2013). M. Kumar M. Kumar XGBoost, 2D-object recognition using shape descriptors and extreme gradient boosting classifier, in Computational Methods and Data Engineering, Springer 2021 207 222. Blei, Kucukelbir, McAuliffe (b0025) 2017; 112 Ma, Gao (b0180) 2020; 97 Ma, Gao (b0175) 2020; 196 Li, Lei, Wang, Jiang, Liu (b0165) 2021; 101 Yang, Chen, Li, Wang (b0215) 2021 Chhabra, Garg, Kumar (b0055) 2020; 32 Li, Xu (b0150) 2001; 14 Katuwal, Suganthan (b0130) 2019; 85 Ma, Teng (b0170) 2019; 80 Yin, Chen, Tang, Dong, Li (b0230) 2022; 586 Golub, Slonim, Tamayo, Huard, Gaasenbeek, Mesirov, Coller, Loh, Downing, Caligiuri, Bloomfield, Lander (b0080) 1999; 286 M. Arjovsky, S. Chintala, L. Bottou, Wasserstein generative adversarial networks, in: International conference on machine learning, PMLR, 2017, pp. 214-223. Leng, Wang, Qin, Li (b0145) 2019; 504 Li, Li, Liu (b0160) 2017; 53 Harari, Katz (b0095) 2022; 582 Garg, Garg, Kumar (b0065) 2018; 77 Huang, Ye, Zhang, Yang, Zhu, Yang (b0100) 2021; 573 N. (b0035) 2014; 159 Muharram, Smith (b0185) 2005; 17 Wang, Li, Zhao (b0210) 2022; 602 Zhang, Han, Xu, Wang (b0245) 2021; 557 A.D. Cherniack, H. Shen, V. Walter, C. Stewart, B.A. Murray, R. Bowlby, X. Hu, S. Ling, R.A. Soslow, R.R. Broaddus, R.E. Zuna, G. Robertson, P.W. Laird, R. Kucherlapati, G.B. Mills, N. Cancer Genome Atlas Research, J.N. Weinstein, J. Zhang, R. Akbani, D.A. Levine, Integrated Molecular Characterization of Uterine Carcinosarcoma, Cancer Cell, 31 (2017) 411-423. Alon, Barkai, Notterman, Gish, Ybarra, Mack, Levine (b0005) 1999; 96 Chen, Fan, Yang, Zhou, Zhu, Li (b0040) 2022; 596 Yang, Wu, Huang, Zhang, Wan, Lai (b0220) 2022; 618 Li, Liu, Liu, Chen, Wan, Cui (b0155) 2019; 81 Jin, Tan, Jiang (b0125) 2020; 2020 Yujian, Bo, Xinwu, Yaozong, Houjun (b0240) 2011; 22 Gao, Hou, Qin, Chen, Liu, Zhu, Zhang, Shao (b0060) 2020 G. Ishaan, F. Ahmed, M. Arjovsky, V. Dumoulin, A. Courville, Improved Training of Wasserstein GANs, in: I. Guyon, U.V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, R. Garnett (Eds.) Advances in Neural Information Processing Systems 30, 2017. N. Cancer Genome Atlas Research (b0030) 2014; 511 Jiang, Zheng, Tan, Tang, Zhou (b0115) 2017 Jin, Liu, Chen (b0120) 2022; 612 Gupta, Mohan, Kumar (b0090) 2021; 28 Ghazouani (b0075) 2021; 103 Chen, Guestrin, M. (b0045) 2016 Binh, Xue, Zhang (b0020) 2016; 8 Walker, Zhang, Zhong, Zhou, Baagyere (b0205) 2022; 605 Sarica, Cerasa, Quattrone (b0195) 2017; 9 M. Yin, W.T. Huang, J.B. Gao, I. Assoc Advancement Artificial, Shared Generative Latent Representation Learning for Multi-View Clustering, in: Thirty-Fourth Aaai Conference on Artificial Intelligence, the Thirty-Second Innovative Applications of Artificial Intelligence Conference and the Tenth Aaai Symposium on Educational Advances in Artificial Intelligence, 2020, pp. 6688-6695. Ontivero-Ortega, Lage-Castellanos, Valente, Goebel, Valdes-Sosa (b0190) 2017; 163 Gehlot, Gupta, Gupta (b0070) 2021; 72 Shaheed, Mao, Qureshi, Kumar, Hussain, Ullah, Zhang (b0200) 2022; 191 Ye, Bors (b0225) 2021; 567 Bansal, Kumar, Kumar, Kumar (b0015) 2021; 25 I.J. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, Y. Bengio, Generative Adversarial Nets, in: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence, K.Q. Weinberger (Eds.) Advances in Neural Information Processing Systems 27, 2014, pp. 2672-2680. Islam, Abdel-Aty, Cai, Yuan (b0110) 2021; 151 Ma (10.1016/j.ins.2023.01.133_b0180) 2020; 97 10.1016/j.ins.2023.01.133_b0105 Ma (10.1016/j.ins.2023.01.133_b0175) 2020; 196 Ghazouani (10.1016/j.ins.2023.01.133_b0075) 2021; 103 10.1016/j.ins.2023.01.133_b0140 Zhu (10.1016/j.ins.2023.01.133_b0250) 2016; 36 Chen (10.1016/j.ins.2023.01.133_b0045) 2016 Sarica (10.1016/j.ins.2023.01.133_b0195) 2017; 9 Garg (10.1016/j.ins.2023.01.133_b0065) 2018; 77 Li (10.1016/j.ins.2023.01.133_b0155) 2019; 81 Yin (10.1016/j.ins.2023.01.133_b0230) 2022; 586 Wang (10.1016/j.ins.2023.01.133_b0210) 2022; 602 Yujian (10.1016/j.ins.2023.01.133_b0240) 2011; 22 Chhabra (10.1016/j.ins.2023.01.133_b0055) 2020; 32 Jin (10.1016/j.ins.2023.01.133_b0125) 2020; 2020 Yang (10.1016/j.ins.2023.01.133_b0215) 2021 10.1016/j.ins.2023.01.133_b0135 Jiang (10.1016/j.ins.2023.01.133_b0115) 2017 Katuwal (10.1016/j.ins.2023.01.133_b0130) 2019; 85 10.1016/j.ins.2023.01.133_b0050 Ontivero-Ortega (10.1016/j.ins.2023.01.133_b0190) 2017; 163 10.1016/j.ins.2023.01.133_b0010 Huang (10.1016/j.ins.2023.01.133_b0100) 2021; 573 Li (10.1016/j.ins.2023.01.133_b0150) 2001; 14 Jin (10.1016/j.ins.2023.01.133_b0120) 2022; 612 Harari (10.1016/j.ins.2023.01.133_b0095) 2022; 582 Walker (10.1016/j.ins.2023.01.133_b0205) 2022; 605 Alon (10.1016/j.ins.2023.01.133_b0005) 1999; 96 Bansal (10.1016/j.ins.2023.01.133_b0015) 2021; 25 Binh (10.1016/j.ins.2023.01.133_b0020) 2016; 8 Golub (10.1016/j.ins.2023.01.133_b0080) 1999; 286 Gao (10.1016/j.ins.2023.01.133_b0060) 2020 10.1016/j.ins.2023.01.133_b0085 Ye (10.1016/j.ins.2023.01.133_b0225) 2021; 567 N. Cancer Genome Atlas Research (10.1016/j.ins.2023.01.133_b0030) 2014; 511 Ma (10.1016/j.ins.2023.01.133_b0170) 2019; 80 Gupta (10.1016/j.ins.2023.01.133_b0090) 2021; 28 Shaheed (10.1016/j.ins.2023.01.133_b0200) 2022; 191 Li (10.1016/j.ins.2023.01.133_b0165) 2021; 101 Blei (10.1016/j.ins.2023.01.133_b0025) 2017; 112 Yang (10.1016/j.ins.2023.01.133_b0220) 2022; 618 Islam (10.1016/j.ins.2023.01.133_b0110) 2021; 151 Gehlot (10.1016/j.ins.2023.01.133_b0070) 2021; 72 10.1016/j.ins.2023.01.133_b0235 N. (10.1016/j.ins.2023.01.133_b0035) 2014; 159 Muharram (10.1016/j.ins.2023.01.133_b0185) 2005; 17 Li (10.1016/j.ins.2023.01.133_b0160) 2017; 53 Zhang (10.1016/j.ins.2023.01.133_b0245) 2021; 557 Leng (10.1016/j.ins.2023.01.133_b0145) 2019; 504 Chen (10.1016/j.ins.2023.01.133_b0040) 2022; 596 |
| References_xml | – volume: 96 start-page: 6745 year: 1999 end-page: 6750 ident: b0005 article-title: Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays publication-title: PNAS – volume: 53 start-page: 551 year: 2017 end-page: 577 ident: b0160 article-title: Recent advances in feature selection and its applications publication-title: Knowl. Inf. Syst. – volume: 14 start-page: 253 year: 2001 end-page: 257 ident: b0150 article-title: Feature space theory - a mathematical foundation for data mining publication-title: Knowl.-Based Syst. – reference: D.P. Kingma, M. Welling, Auto-encoding variational bayes, arXiv preprint arXiv:1312.6114, (2013). – year: 2021 ident: b0215 article-title: Subtype-GAN: a deep learning approach for integrative cancer subtyping of multi-omics data publication-title: Bioinformatics – volume: 103 year: 2021 ident: b0075 article-title: A genetic programming-based feature selection and fusion for facial expression recognition publication-title: Appl. Soft Comput. – volume: 586 start-page: 374 year: 2022 end-page: 390 ident: b0230 article-title: Adaptive feature selection with shapley and hypothetical testing: Case study of EEG feature engineering publication-title: Inf. Sci. – volume: 612 start-page: 745 year: 2022 end-page: 758 ident: b0120 article-title: An efficient deep neural network framework for COVID-19 lung infection segmentation publication-title: Inf. Sci. – year: 2016 ident: b0045 article-title: Assoc Comp, XGBoost: A Scalable Tree Boosting publication-title: System – volume: 163 start-page: 471 year: 2017 end-page: 479 ident: b0190 article-title: Fast Gaussian Naive Bayes for searchlight classification analysis publication-title: Neuroimage – volume: 81 year: 2019 ident: b0155 article-title: On Improving the accuracy with Auto-Encoder on Conjunctivitis publication-title: Appl. Soft Comput. – volume: 151 year: 2021 ident: b0110 article-title: Crash data augmentation using variational autoencoder publication-title: Accid. Anal. Prev. – volume: 17 start-page: 1518 year: 2005 end-page: 1528 ident: b0185 article-title: Evolutionary constructive induction publication-title: IEEE Trans. Knowl. Data Eng. – volume: 602 start-page: 259 year: 2022 end-page: 268 ident: b0210 article-title: Corporate finance risk prediction based on LightGBM publication-title: Inf. Sci. – volume: 25 start-page: 4423 year: 2021 end-page: 4432 ident: b0015 article-title: An efficient technique for object recognition using Shi-Tomasi corner detection algorithm publication-title: Soft. Comput. – reference: M. Yin, W.T. Huang, J.B. Gao, I. Assoc Advancement Artificial, Shared Generative Latent Representation Learning for Multi-View Clustering, in: Thirty-Fourth Aaai Conference on Artificial Intelligence, the Thirty-Second Innovative Applications of Artificial Intelligence Conference and the Tenth Aaai Symposium on Educational Advances in Artificial Intelligence, 2020, pp. 6688-6695. – volume: 77 start-page: 26545 year: 2018 end-page: 26561 ident: b0065 article-title: Underwater image enhancement using blending of CLAHE and percentile methodologies publication-title: Multimed. Tools Appl. – volume: 8 start-page: 3 year: 2016 end-page: 15 ident: b0020 article-title: Genetic programming for feature construction and selection in classification on high-dimensional data publication-title: Memetic Computing – volume: 80 start-page: 687 year: 2019 end-page: 699 ident: b0170 article-title: A hybrid multiple feature construction approach for classification using Genetic Programming publication-title: Appl. Soft Comput. – volume: 557 start-page: 302 year: 2021 end-page: 316 ident: b0245 article-title: HOBA: A novel feature engineering methodology for credit card fraud detection with a deep learning architecture publication-title: Inf. Sci. – volume: 511 start-page: 543 year: 2014 end-page: 550 ident: b0030 article-title: Comprehensive molecular profiling of lung adenocarcinoma publication-title: Nature – volume: 28 start-page: 2209 year: 2021 end-page: 2223 ident: b0090 article-title: A study on source device attribution using still images publication-title: Arch. Comput. Meth. Eng. – volume: 97 year: 2020 ident: b0180 article-title: Designing genetic programming classifiers with feature selection and feature construction publication-title: Appl. Soft Comput. – volume: 101 year: 2021 ident: b0165 article-title: Embedded stacked group sparse autoencoder ensemble with L1 regularization and manifold reduction publication-title: Appl. Soft Comput. – volume: 567 start-page: 216 year: 2021 end-page: 236 ident: b0225 article-title: Learning joint latent representations based on information maximization publication-title: Inf. Sci. – reference: G. Ishaan, F. Ahmed, M. Arjovsky, V. Dumoulin, A. Courville, Improved Training of Wasserstein GANs, in: I. Guyon, U.V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, R. Garnett (Eds.) Advances in Neural Information Processing Systems 30, 2017. – year: 2020 ident: b0060 article-title: Zero-VAE-GAN: Generating Unseen Features for Generalized and Transductive Zero-Shot Learning publication-title: IEEE Trans. Image Process. – volume: 36 start-page: 973 year: 2016 end-page: 989 ident: b0250 article-title: Logistic Regression-Based Trichotomous Classification Tree and Its Application in Medical Diagnosis publication-title: Med. Decis. Making – volume: 32 start-page: 2725 year: 2020 end-page: 2733 ident: b0055 article-title: Content-based image retrieval system using ORB and SIFT features publication-title: Neural Comput. & Applic. – reference: M. Kumar M. Kumar XGBoost, 2D-object recognition using shape descriptors and extreme gradient boosting classifier, in Computational Methods and Data Engineering, Springer 2021 207 222. – volume: 582 start-page: 398 year: 2022 end-page: 414 ident: b0095 article-title: Automatic features generation and selection from external sources: A DBpedia use case publication-title: Inf. Sci. – volume: 573 start-page: 345 year: 2021 end-page: 359 ident: b0100 article-title: Double L2, p-norm based PCA for feature extraction publication-title: Inf. Sci. – volume: 618 start-page: 400 year: 2022 end-page: 416 ident: b0220 article-title: Orthogonal autoencoder regression for image classification publication-title: Inf. Sci. – volume: 72 year: 2021 ident: b0070 article-title: A CNN-based unified framework utilizing projection loss in unison with label noise handling for multiple Myeloma cancer diagnosis publication-title: Med. Image Anal. – volume: 196 year: 2020 ident: b0175 article-title: A filter-based feature construction and feature selection approach for classification using Genetic Programming publication-title: Knowl.-Based Syst. – reference: M. Arjovsky, S. Chintala, L. Bottou, Wasserstein generative adversarial networks, in: International conference on machine learning, PMLR, 2017, pp. 214-223. – reference: A.D. Cherniack, H. Shen, V. Walter, C. Stewart, B.A. Murray, R. Bowlby, X. Hu, S. Ling, R.A. Soslow, R.R. Broaddus, R.E. Zuna, G. Robertson, P.W. Laird, R. Kucherlapati, G.B. Mills, N. Cancer Genome Atlas Research, J.N. Weinstein, J. Zhang, R. Akbani, D.A. Levine, Integrated Molecular Characterization of Uterine Carcinosarcoma, Cancer Cell, 31 (2017) 411-423. – volume: 159 start-page: 676 year: 2014 end-page: 690 ident: b0035 article-title: Cancer Genome Atlas Research, Integrated genomic characterization of papillary thyroid carcinoma publication-title: Cell – volume: 85 year: 2019 ident: b0130 article-title: Stacked autoencoder based deep random vector functional link neural network for classification publication-title: Appl. Soft Comput. – volume: 9 year: 2017 ident: b0195 article-title: Random forest algorithm for the classification of neuroimaging data in Alzheimer's Disease: A systematic review publication-title: Front. Aging Neurosci. – volume: 191 year: 2022 ident: b0200 article-title: DS-CNN: A pre-trained Xception model based on depth-wise separable convolutional neural network for finger vein recognition publication-title: Expert Syst. Appl. – volume: 605 start-page: 267 year: 2022 end-page: 285 ident: b0205 article-title: Variational cold-start resistant recommendation publication-title: Inf. Sci. – volume: 112 start-page: 859 year: 2017 end-page: 877 ident: b0025 article-title: Variational Inference: A Review for Statisticians publication-title: J. Am. Stat. Assoc. – volume: 286 start-page: 531 year: 1999 end-page: 537 ident: b0080 article-title: Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring publication-title: Science – volume: 596 start-page: 280 year: 2022 end-page: 303 ident: b0040 article-title: Stacked maximal quality-driven autoencoder: Deep feature representation for soft analyzer and its application on industrial processes publication-title: Inf. Sci. – volume: 22 start-page: 276 year: 2011 end-page: 289 ident: b0240 article-title: Multiconlitron: a general piecewise linear classifier publication-title: IEEE Trans. Neural Netw. – year: 2017 ident: b0115 article-title: Variational deep embedding: An unsupervised and generative approach to clustering publication-title: Proc. 26th Int. Joint Conf. Artif. Intell. – volume: 2020 year: 2020 ident: b0125 article-title: Generative adversarial network technologies and applications in computer vision publication-title: Comput. Intell. Neurosci. – reference: I.J. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, Y. Bengio, Generative Adversarial Nets, in: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence, K.Q. Weinberger (Eds.) Advances in Neural Information Processing Systems 27, 2014, pp. 2672-2680. – volume: 504 start-page: 435 year: 2019 end-page: 448 ident: b0145 article-title: An effective method to determine whether a point is within a convex hull and its generalized convex polyhedron classifier publication-title: Inf. Sci. – volume: 17 start-page: 1518 year: 2005 ident: 10.1016/j.ins.2023.01.133_b0185 article-title: Evolutionary constructive induction publication-title: IEEE Trans. Knowl. Data Eng. doi: 10.1109/TKDE.2005.182 – volume: 85 year: 2019 ident: 10.1016/j.ins.2023.01.133_b0130 article-title: Stacked autoencoder based deep random vector functional link neural network for classification publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2019.105854 – volume: 196 year: 2020 ident: 10.1016/j.ins.2023.01.133_b0175 article-title: A filter-based feature construction and feature selection approach for classification using Genetic Programming publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2020.105806 – volume: 80 start-page: 687 year: 2019 ident: 10.1016/j.ins.2023.01.133_b0170 article-title: A hybrid multiple feature construction approach for classification using Genetic Programming publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2019.04.039 – volume: 9 year: 2017 ident: 10.1016/j.ins.2023.01.133_b0195 article-title: Random forest algorithm for the classification of neuroimaging data in Alzheimer's Disease: A systematic review publication-title: Front. Aging Neurosci. doi: 10.3389/fnagi.2017.00329 – ident: 10.1016/j.ins.2023.01.133_b0010 – volume: 605 start-page: 267 year: 2022 ident: 10.1016/j.ins.2023.01.133_b0205 article-title: Variational cold-start resistant recommendation publication-title: Inf. Sci. doi: 10.1016/j.ins.2022.05.025 – volume: 191 year: 2022 ident: 10.1016/j.ins.2023.01.133_b0200 article-title: DS-CNN: A pre-trained Xception model based on depth-wise separable convolutional neural network for finger vein recognition publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2021.116288 – ident: 10.1016/j.ins.2023.01.133_b0085 – ident: 10.1016/j.ins.2023.01.133_b0140 doi: 10.1007/978-981-15-6876-3_16 – volume: 97 year: 2020 ident: 10.1016/j.ins.2023.01.133_b0180 article-title: Designing genetic programming classifiers with feature selection and feature construction publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2020.106826 – volume: 151 year: 2021 ident: 10.1016/j.ins.2023.01.133_b0110 article-title: Crash data augmentation using variational autoencoder publication-title: Accid. Anal. Prev. doi: 10.1016/j.aap.2020.105950 – volume: 112 start-page: 859 year: 2017 ident: 10.1016/j.ins.2023.01.133_b0025 article-title: Variational Inference: A Review for Statisticians publication-title: J. Am. Stat. Assoc. doi: 10.1080/01621459.2017.1285773 – volume: 101 year: 2021 ident: 10.1016/j.ins.2023.01.133_b0165 article-title: Embedded stacked group sparse autoencoder ensemble with L1 regularization and manifold reduction publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2020.107003 – ident: 10.1016/j.ins.2023.01.133_b0135 – volume: 163 start-page: 471 year: 2017 ident: 10.1016/j.ins.2023.01.133_b0190 article-title: Fast Gaussian Naive Bayes for searchlight classification analysis publication-title: Neuroimage doi: 10.1016/j.neuroimage.2017.09.001 – volume: 77 start-page: 26545 year: 2018 ident: 10.1016/j.ins.2023.01.133_b0065 article-title: Underwater image enhancement using blending of CLAHE and percentile methodologies publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-018-5878-8 – volume: 511 start-page: 543 year: 2014 ident: 10.1016/j.ins.2023.01.133_b0030 article-title: Comprehensive molecular profiling of lung adenocarcinoma publication-title: Nature doi: 10.1038/nature13385 – volume: 14 start-page: 253 year: 2001 ident: 10.1016/j.ins.2023.01.133_b0150 article-title: Feature space theory - a mathematical foundation for data mining publication-title: Knowl.-Based Syst. doi: 10.1016/S0950-7051(01)00103-4 – volume: 96 start-page: 6745 year: 1999 ident: 10.1016/j.ins.2023.01.133_b0005 article-title: Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays publication-title: PNAS doi: 10.1073/pnas.96.12.6745 – ident: 10.1016/j.ins.2023.01.133_b0235 doi: 10.1609/aaai.v34i04.6146 – volume: 32 start-page: 2725 year: 2020 ident: 10.1016/j.ins.2023.01.133_b0055 article-title: Content-based image retrieval system using ORB and SIFT features publication-title: Neural Comput. & Applic. doi: 10.1007/s00521-018-3677-9 – volume: 72 year: 2021 ident: 10.1016/j.ins.2023.01.133_b0070 article-title: A CNN-based unified framework utilizing projection loss in unison with label noise handling for multiple Myeloma cancer diagnosis publication-title: Med. Image Anal. doi: 10.1016/j.media.2021.102099 – volume: 286 start-page: 531 year: 1999 ident: 10.1016/j.ins.2023.01.133_b0080 article-title: Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring publication-title: Science doi: 10.1126/science.286.5439.531 – year: 2017 ident: 10.1016/j.ins.2023.01.133_b0115 article-title: Variational deep embedding: An unsupervised and generative approach to clustering publication-title: Proc. 26th Int. Joint Conf. Artif. Intell. – volume: 28 start-page: 2209 year: 2021 ident: 10.1016/j.ins.2023.01.133_b0090 article-title: A study on source device attribution using still images publication-title: Arch. Comput. Meth. Eng. doi: 10.1007/s11831-020-09452-y – volume: 8 start-page: 3 year: 2016 ident: 10.1016/j.ins.2023.01.133_b0020 article-title: Genetic programming for feature construction and selection in classification on high-dimensional data publication-title: Memetic Computing doi: 10.1007/s12293-015-0173-y – ident: 10.1016/j.ins.2023.01.133_b0105 – volume: 573 start-page: 345 year: 2021 ident: 10.1016/j.ins.2023.01.133_b0100 article-title: Double L2, p-norm based PCA for feature extraction publication-title: Inf. Sci. doi: 10.1016/j.ins.2021.05.079 – volume: 25 start-page: 4423 year: 2021 ident: 10.1016/j.ins.2023.01.133_b0015 article-title: An efficient technique for object recognition using Shi-Tomasi corner detection algorithm publication-title: Soft. Comput. doi: 10.1007/s00500-020-05453-y – volume: 586 start-page: 374 year: 2022 ident: 10.1016/j.ins.2023.01.133_b0230 article-title: Adaptive feature selection with shapley and hypothetical testing: Case study of EEG feature engineering publication-title: Inf. Sci. doi: 10.1016/j.ins.2021.11.063 – ident: 10.1016/j.ins.2023.01.133_b0050 – volume: 159 start-page: 676 year: 2014 ident: 10.1016/j.ins.2023.01.133_b0035 article-title: Cancer Genome Atlas Research, Integrated genomic characterization of papillary thyroid carcinoma publication-title: Cell doi: 10.1016/j.cell.2014.09.050 – volume: 53 start-page: 551 year: 2017 ident: 10.1016/j.ins.2023.01.133_b0160 article-title: Recent advances in feature selection and its applications publication-title: Knowl. Inf. Syst. doi: 10.1007/s10115-017-1059-8 – volume: 618 start-page: 400 year: 2022 ident: 10.1016/j.ins.2023.01.133_b0220 article-title: Orthogonal autoencoder regression for image classification publication-title: Inf. Sci. doi: 10.1016/j.ins.2022.10.068 – volume: 36 start-page: 973 year: 2016 ident: 10.1016/j.ins.2023.01.133_b0250 article-title: Logistic Regression-Based Trichotomous Classification Tree and Its Application in Medical Diagnosis publication-title: Med. Decis. Making doi: 10.1177/0272989X15618658 – volume: 103 year: 2021 ident: 10.1016/j.ins.2023.01.133_b0075 article-title: A genetic programming-based feature selection and fusion for facial expression recognition publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2021.107173 – volume: 567 start-page: 216 year: 2021 ident: 10.1016/j.ins.2023.01.133_b0225 article-title: Learning joint latent representations based on information maximization publication-title: Inf. Sci. doi: 10.1016/j.ins.2021.03.007 – year: 2020 ident: 10.1016/j.ins.2023.01.133_b0060 article-title: Zero-VAE-GAN: Generating Unseen Features for Generalized and Transductive Zero-Shot Learning publication-title: IEEE Trans. Image Process. – volume: 596 start-page: 280 year: 2022 ident: 10.1016/j.ins.2023.01.133_b0040 article-title: Stacked maximal quality-driven autoencoder: Deep feature representation for soft analyzer and its application on industrial processes publication-title: Inf. Sci. doi: 10.1016/j.ins.2022.02.049 – volume: 582 start-page: 398 year: 2022 ident: 10.1016/j.ins.2023.01.133_b0095 article-title: Automatic features generation and selection from external sources: A DBpedia use case publication-title: Inf. Sci. doi: 10.1016/j.ins.2021.09.036 – year: 2021 ident: 10.1016/j.ins.2023.01.133_b0215 article-title: Subtype-GAN: a deep learning approach for integrative cancer subtyping of multi-omics data publication-title: Bioinformatics doi: 10.1093/bioinformatics/btab109 – volume: 2020 year: 2020 ident: 10.1016/j.ins.2023.01.133_b0125 article-title: Generative adversarial network technologies and applications in computer vision publication-title: Comput. Intell. Neurosci. doi: 10.1155/2020/1459107 – volume: 504 start-page: 435 year: 2019 ident: 10.1016/j.ins.2023.01.133_b0145 article-title: An effective method to determine whether a point is within a convex hull and its generalized convex polyhedron classifier publication-title: Inf. Sci. doi: 10.1016/j.ins.2019.07.065 – volume: 81 year: 2019 ident: 10.1016/j.ins.2023.01.133_b0155 article-title: On Improving the accuracy with Auto-Encoder on Conjunctivitis publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2019.105489 – volume: 612 start-page: 745 year: 2022 ident: 10.1016/j.ins.2023.01.133_b0120 article-title: An efficient deep neural network framework for COVID-19 lung infection segmentation publication-title: Inf. Sci. doi: 10.1016/j.ins.2022.08.059 – volume: 602 start-page: 259 year: 2022 ident: 10.1016/j.ins.2023.01.133_b0210 article-title: Corporate finance risk prediction based on LightGBM publication-title: Inf. Sci. doi: 10.1016/j.ins.2022.04.058 – volume: 22 start-page: 276 year: 2011 ident: 10.1016/j.ins.2023.01.133_b0240 article-title: Multiconlitron: a general piecewise linear classifier publication-title: IEEE Trans. Neural Netw. doi: 10.1109/TNN.2010.2094624 – year: 2016 ident: 10.1016/j.ins.2023.01.133_b0045 article-title: Assoc Comp, XGBoost: A Scalable Tree Boosting publication-title: System – volume: 557 start-page: 302 year: 2021 ident: 10.1016/j.ins.2023.01.133_b0245 article-title: HOBA: A novel feature engineering methodology for credit card fraud detection with a deep learning architecture publication-title: Inf. Sci. doi: 10.1016/j.ins.2019.05.023 |
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