Application of discriminant analysis and neutral networks to forecasting the financial standing of farms with consideration the influence of the time
2006
Kisielinska, J.,Szkola Glowna Gospodarstwa Wiejskiego, Warszawa (Poland). Katedra Ekonometrii i Informatyki
The aim of the research was to determinate a linear discriminant function and neural network that could be applied for classification of farms. The result of classification was forecasting financial situation of them, based on set of many variables, which including financial indicators. Models were built separately for each year, but they were verified in the rest. The additional aims were to determine the set of indicators with large forecasting ability, and to compare two classification methods - linear discriminant function and neural network
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