Selection of the company development option using machine learning methods
For any company, the development option selection becomes a challenging task, given the changeable economic environment, the lack of information on the competitive behaviour, and the determination of variables that affect the company’s activity. In this context, it is considered preferable to use machine learning methods that select a model suitable for the acceptable option selection based on learning data. The purpose of the study is to develop the option selection method. The study situations include the strategies for market expansion (option 1), reduction (option 2) and survival (option 3). Six indicators that characterize both external and internal aspects of company functioning affect the development option selection. The linear discriminant analysis, k-Nearest Neighbor, support vector machine and decision trees are used as machine learning methods for solving the task. The most accurate result based on the learning data is provided by the support vector machine, which is used upon selection of a company development option.