Inverse Problem Approach to Machine Learning with Application in the Option Price Correction

We investigate a new method in learning to fix the existence of an unsuitable subfunction of a general system. We assume this subfunction is dependent on the system input variables. In this process, we put a learner instead of the unsuitable subfunction and train it by a training model obtained from...

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Bibliographic Details
Published in:Optical memory & neural networks 2022-03, Vol.31 (1), p.46-58
Main Authors: Pourmohammad Azizi, S., Jafari, Hossein, Faghan, Yaser, Neisy, Abdolsadeh
Format: Article
Language:English
Subjects:
Complexity
Computer Science
Information Storage and Retrieval
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Summary:We investigate a new method in learning to fix the existence of an unsuitable subfunction of a general system. We assume this subfunction is dependent on the system input variables. In this process, we put a learner instead of the unsuitable subfunction and train it by a training model obtained from inverse problems and fractional derivatives, respectively. Finally, we implemented this method on a simple financial model and examined the results with simulated and real data.
ISSN:1060-992X
1934-7898
DOI:10.3103/S1060992X22010088