A Hybrid Machine Learning System to impute and classify a component-based robot
-
1
Universidad de Burgos
info
Revista:
Logic Journal of the IGPL
ISSN: 1367-0751, 1368-9894
Año de publicación: 2022
Tipo: Artículo
Otras publicaciones en: Logic Journal of the IGPL
Referencias bibliográficas
- Arroyo, (2020), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 86
- Basurto, (2020), Computers and Electrical Engineering, 87, 10.1016/j.compeleceng.2020.106766
- Basurto, (2021), Neurocomputing, pp. 419
- Basurto, (2020), 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019), pp. 241, 10.1007/978-3-030-20055-8_23
- Boser, (1992), Proceedings of the Fifth Annual Workshop on Computational Learning Theory, COLT ‘92, pp. 144, 10.1145/130385.130401
- Caliński, (1974), Communications in Statistics-Theory and Methods, 3, pp. 1, 10.1080/03610927408827101
- Cerqueira, (2016), Advances in Intelligent Data Analysis XV, pp. 393, 10.1007/978-3-319-46349-0_35
- Chawla, (2002), Journal of Artificial Intelligence Research, 16, pp. 321, 10.1613/jair.953
- Cortes, (1995), Machine Learning, 20, pp. 273, 10.1007/BF00994018
- Das, (2018), Pattern Recognition, 81, pp. 674, 10.1016/j.patcog.2018.03.008
- Davies, (1979), IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 224
- Day, (1984), Journal of Classification, 1, pp. 7, 10.1007/BF01890115
- Devi, (2019), Connection Science, 31, pp. 105, 10.1080/09540091.2018.1560394
- Ester, (1996), KDD-96: Proceedings, pp. 226
- García-Laencina, (2010), Neural Computing and Applications, 19, pp. 263, 10.1007/s00521-009-0295-6
- García-Laencina, (2010), Neural Computing and Applications, 19, pp. 263, 10.1007/s00521-009-0295-6
- Han, (2005), Lecture Notes in Computer Science, pp. 878
- Jain, (1999), ACM Computing Surveys, 31, pp. 264, 10.1145/331499.331504
- Jove, (2020), Logic Journal of the IGPL, 10.1093/jigpal/jzz057
- Hamidreza Kasaei, (2018), Neurocomputing, 291, pp. 151, 10.1016/j.neucom.2018.02.066
- Khalastchi, (2018), ACM Computing Surveys, 51, pp. 1, 10.1145/3146389
- Lippmann, (1989), IEEE Communications Magazine, 27, pp. 47, 10.1109/35.41401
- MacQueen, (1967), Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, volume 1, pp. 281
- Neter, (1996), Applied Linear Statistical Models
- University of Yale, (2017), Linear Regression
- Park, (1991), Neural Computation, 3, pp. 246, 10.1162/neco.1991.3.2.246
- Pearson, (1908), Biometrika, 6, pp. 59, 10.1093/biomet/6.1.59
- Pigott, (2001), Educational Research and Evaluation, 7, pp. 353, 10.1076/edre.7.4.353.8937
- Rousseeuw, (1987), Journal of Computational and Applied Mathematics, 20, pp. 53, 10.1016/0377-0427(87)90125-7
- Shin, (2005), Computers and Industrial Engineering, 48, pp. 395, 10.1016/j.cie.2005.01.009
- Sokal, (1962), Taxon, 11, pp. 33, 10.2307/1217208
- Suykens, (1999), Neural Processing Letters, 9, pp. 293, 10.1023/A:1018628609742
- Syafrudin, (2018), Applied Sciences, 9, pp. 84, 10.3390/app9010084
- Tibshirani, (2001), Journal of the Royal Statistical Society: Series B (Statistical Methodology), 63, pp. 411, 10.1111/1467-9868.00293
- Wienke, (2011), 2011 IEEE/SICE International Symposium on System Integration (SII), pp. 1183, 10.1109/SII.2011.6147617
- Wienke, (2017), Advanced Robotics, 31, pp. 1177, 10.1080/01691864.2017.1395360
- Wienke, (2018), Framework-Level Resource Awareness in Robotics and Intelligent Systems
- Wienke, (2016), Towards Autonomous Robotic Systems, pp. 339, 10.1007/978-3-319-40379-3_35
- Wienke, (2018), Proceedings—2nd IEEE International Conference on Robotic Computing, IRC 2018, volume 2018-January, pp. 25
- Wienke, A Fault Detection Data Set for Performance Bugs in Component-Based Robotic Systems
- Wienke, (2016), Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on, pp. 3291, 10.1109/IROS.2016.7759507