Bankruptcy prediction in Visegrad group countries using multiple discriminant analysis

Partial Least Square Discriminant Analysis for bankruptcy prediction

Unemployment and Labor Market Policy in Visegrad Group Countries

In the recent years, an economic crisis has appeared in most economies. It affected the labor market situation. This article refers to the changes in the labor markets of the Visegrad Group countries. The analysis concerns the relations between the economic crisis, the level and structure of unemployment (taking into account the situation of women and young people as the groups strongly exposed...

Development of Agricultural Trade of Visegrad Group Countries in Relation to EU and Third Countries

Despite the continually growing value of agricultural trade of the Czech Republic, Hungary, Slovakia and Poland, agricultural trade in the case of all of the countries of the Visegrad group represents only a marginal part of the total merchandise trade. The agricultural trade of the individual analyzed countries is, both in terms of the commodity structure as well as the territorial structure, ...

A comparison of group prediction approaches in longitudinal discriminant analysis

Longitudinal discriminant analysis (LoDA) can be used to classify patients into prognostic groups based on their clinical history, which often involves longitudinal measurements of various clinically relevant markers. Patients' longitudinal data is first modelled using multivariate generalised linear mixed models, allowing markers of different types (e.g. continuous, binary, counts) to be model...

Bankruptcy Prediction Using Feature Projection

Bankruptcy prediction has been an important decision-making process for nancial analysts. One of the most common approaches for the bankruptcy prediction problem is the Discrim-inant Analysis. Also, the k-Nearest Neighbor classiier is very successful in such domains. This paper proposes a Feature Projection based classiication algorithm, and explores its applicability to the problem of predicti...