TY - GEN
T1 - Performance of inductive method of model self-organization with incomplete model and noisy data
AU - Ponomareva, Natalia
AU - Alexandrov, Mikhail
AU - Gelbukh, Alexander
PY - 2008
Y1 - 2008
N2 - Inductive method of model self-organization (IMMSO) developed in 80s by A. Ivakhnenko is an evolutionary machine learning algorithm, which allows selecting a model of optimal complexity that describes or explains a limited number of observation data when any a priori information is absent or is highly insufficient. In this paper, we study the performance of IMMSO to reveal a model in a given class with different volumes of data, contributions of unaccounted components, and levels of noise. As a simple case study, we consider artificial observation data: the sum of a quadratic parabola and cosine; model class under consideration is a polynomial series. The results are interpreted in the terms of signal-noise ratio.
AB - Inductive method of model self-organization (IMMSO) developed in 80s by A. Ivakhnenko is an evolutionary machine learning algorithm, which allows selecting a model of optimal complexity that describes or explains a limited number of observation data when any a priori information is absent or is highly insufficient. In this paper, we study the performance of IMMSO to reveal a model in a given class with different volumes of data, contributions of unaccounted components, and levels of noise. As a simple case study, we consider artificial observation data: the sum of a quadratic parabola and cosine; model class under consideration is a polynomial series. The results are interpreted in the terms of signal-noise ratio.
UR - http://www.scopus.com/inward/record.url?scp=57849154826&partnerID=8YFLogxK
U2 - 10.1109/MICAI.2008.72
DO - 10.1109/MICAI.2008.72
M3 - Contribución a la conferencia
AN - SCOPUS:57849154826
SN - 9780769534411
T3 - 7th Mexican International Conference on Artificial Intelligence - Proceedings of the Special Session, MICAI 2008
SP - 101
EP - 108
BT - 7th Mexican International Conference on Artificial Intelligence - Proceedings of the Special Session, MICAI 2008
T2 - 7th Mexican International Conference on Artificial Intelligence, MICAI 2008
Y2 - 27 October 2008 through 31 October 2008
ER -