Wpływ wybranych metod uzupełniania brakujących danych na wyniki klasyfikacji obiektów z wykorzystaniem drzew klasyfikacyjnych w przypadku zbiorów dany
Influence of data imputation methods on the results of object classification using classification trees in the case of small data sets – simulation as

Summary/Abstract: Classification tree is an example of the learning algorithm coping with missing values. In the paper some selected missing data techniques are compared by artificially simulating different proportions and mechanisms of missing data using complete data sets mainly from the UCI repository of machine learning databases. The goal of the paper is to assess the influence of these techniques on the results of object classification by means of classification trees in the case of small data sets.

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