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Recently, the following discrimination aware classification problem was introduced: given a labeled dataset and an attribute B, find a classifier with high predictive accuracy that at the same time does not discriminate on the basis of the given attribute B. This problem is motivated by the fact that often available historic data is biased due to discrimination, e.g., when B denotes ethnicity. Using...
This paper presents one of many possibilities of decision theory that can be used in the modelling of the quality of life in a given city in the Czech Republic. Real data sets from citizen questionnaires for the city of Chrudim were analysed, pre-processed, and used in the classification models. Classifier models, on the basis of C5.0, CHAID, C&RT, and C5.0 boosting algorithms were proposed and...
This study focused on comparing the classification performance and accuracy for short-term urban traffic flow condition using decision tree algorithms (CHAID, CART, QUEST and C5.0). In building decision tree models, input variables were multiple roads' traffic flow condition value at current time, while, target variable was a certain road's condition value at future temporal horizon from 5-30 min...
Corporate credit ratings are important financial indicators of investment risks. Traditional credit rating models employ classical econometrics methods with heteroscedasticity adjustments across various industries. In this paper, we propose using machine learning techniques in predicting corporate ratings and demonstrate, empirically, that multiclass machine learning algorithms outperform traditional...
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