Abstract
The paper proposes an approach to solving multiclass pattern recognition problem in a geometric formulation based on convex hulls and convex separable sets (CS-sets). The advantage of the proposed method is the uniqueness of the resulting solution and the uniqueness of assigning each point of the source space to one of the classes. The approach also allows you to uniqelly filter the sourse data for the outliers in the data. Computational experiments using the developed approach were carried out using academic examples and test data from public libraries.
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- 1.
When opening a position on the exchange, the position is constantly re-evaluated at current prices. Accordingly, the maximum loss on the position is the maximum amount of reduction in the value of the position relative to the value of the position when opening.
- 2.
Position hold period is the time from the moment of initial purchase or sale of a certain amount of financial instrument to the moment of reverse in relation to the first trading operation. For more information about the concept of opening and closing positions, see https://www.metatrader5.com/ru/mobile-trading/android/help/trade/positions_manage/open_positions (accessed 01.09.2019).
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Gainanov, D.N., Chernavin, P.F., Rasskazova, V.A., Chernavin, N.P. (2020). Convex Hulls in Solving Multiclass Pattern Recognition Problem. In: Kotsireas, I., Pardalos, P. (eds) Learning and Intelligent Optimization. LION 2020. Lecture Notes in Computer Science(), vol 12096. Springer, Cham. https://doi.org/10.1007/978-3-030-53552-0_35
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