Current research on data stream classification mainly focuses on certain data, in which precise and definite value is usually assumed. However, data with uncertainty is quite natu...
Traditional decision tree classifiers work with data whose values are known and precise. We extend such classifiers to handle data with uncertain information, which originates from...
Smith Tsang, Ben Kao, Kevin Y. Yip, Wai-Shing Ho, ...
The belief decision tree (BDT) approach is a decision tree in an uncertain environment where the uncertainty is represented through the Transferable Belief Model (TBM), one interp...
This paper investigates an extension of classification trees to deal with uncertain information where uncertainty is encoded in possibility theory framework. Class labels in data s...
Ilyes Jenhani, Nahla Ben Amor, Salem Benferhat, Zi...
Classification is one of the most essential tasks in data mining. Unlike other methods, associative classification tries to find all the frequent patterns existing in the input...