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The application of logistic regression to small-sized data sets results in biased estimates and often leads to a complete separation problem. Under the small sample scenario the Firth’s approach to logistic regression or its Bayesian counterpart are known to solve both issues. The main goal of this study is to explore the effectiveness of the best subset variable selection algorithm, applied to both...
Celem artykułu jest zbadanie potencjału wybranych, współcześnie zaproponowanych metod data mining w kontekście prognozowania cen energii elektrycznej na rynku dnia następnego. Szczególny nacisk został położony na zbadanie algorytmu lasów losowych. Prognozy uzyskane metodą lasów losowych porównano z prognozami wygenerowanymi przez model regresji liniowej, model regresji medianowej oraz regresyjną metodę...
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