In the last years, the application of artificial intelligence methods on credit risk assessment
has meant an improvement over classic methods. Small improvements in the systems about …

In the present study, gully erosion susceptibility was evaluated for the area of the Robat Turk
Watershed in Iran. The assessment of gully erosion susceptibility was performed using four …

Previous studies about ensembles of classifiers for bankruptcy prediction and credit scoring
have been presented. In these studies, different ensemble schemes for complex classifiers …

In the area of classification, C4. 5 is a known algorithm widely used to design decision trees.
In this algorithm, a pruning process is carried out to solve the problem of the over-fitting. A …

The theory of Evidence, or Shafer-Dempster theory (DST), has been widely used in
applications. The DST is based on the concept of a basic probability assignment. An …

This paper addresses the classification problem with imperfect data. More precisely, it
extends standard decision trees to handle uncertainty in both building and classification …

Abstract The Random Forest classifier has been considered as an important reference in the
data mining area. The building procedure of its base classifier (a decision tree) is principally …

Variable selection methods play an important role in the field of attribute mining. The Naive
Bayes (NB) classifier is a very simple and popular classification method that yields good …

Decision tree based classification algorithms like C4. 5 and Explore build a single tree from
a data set. The two main purposes of building a decision tree are to extract various …

Predictions made by imprecise-probability models are often indeterminate (that is, set-
valued). Measuring the quality of an indeterminate prediction by a single number is …