Abstract In this data-driven era, where a large number of attributes are often publicly available, redundancy becomes major problem, which leads to storage and computational resource requirement. Feature selection is method for reducing the dimensionality data by removing such redundant or misleading attributes. This optimal feature subsets that can be used further computation like classificati...

This paper considers a multi-period portfolio selection problem imposed by return demand and risk control in a fuzzy investment environment, in which the returns of assets are characterized by fuzzy numbers. A fuzzy lower semi-deviation is originally defined as the risk control of portfolio. A proportion entropy constraint is added as the divergence measure of portfolio. Based on the theories o...

The optimization of investment portfolios is the most important topic in financial decision making, and many relevant models can be found in the literature.  According to importance of portfolio optimization in this paper, deals with novel solution approaches to solve new developed portfolio optimization model. Contrary to previous work, the uncertainty of future retur...

Feature selection (FS) is an important research topic in machine learning. Usually, FS modelled as a bi-objective optimization problem whose objectives are: 1) classification accuracy; 2) number of features. One the main issues real-world applications missing data. Databases with data are likely to be unreliable. Thus, performed on set some also In order directly control this issue plaguing fie...

This paper presents two fuzzy portfolio selection models where the objective is to minimize the downside risk constrained so that a given expected return should be achieved. We assume that the rates of returns on securities are approximated as LR-fuzzy numbers of the same shape, and that the expected return and risk are evaluated by interval-valued means. We establish the relationship between t...

Abstract In this paper, we propose an approach to explore reinsurance optimization for a non-life multi-line insurer through simulation model that combines alternative treaties. Based on the Solvency II framework, maximises both solvency ratio and portfolio performance under user-defined constraints. Data visualisation helps understanding numerical results and, together with concept of Pareto f...