Handling missing attribute values is the greatest challenging process in data analysis. There are so many approaches that can be adopted to handle the missing attributes. In this paper, a comparative analysis is made of an incomplete dataset for future prediction using rough set approach and random tree generation in data mining. The result of simple classification technique (using random tree ...

Single-valued neutrosophic hesitant fuzzy set is a merged form of single-valued neutrosophic sets and hesitant fuzzy sets. This set is a useful tool to handle imprecise, incomplete and inconsistent information existing in multi-attribute decision making problems. In multi-attribute decision making, distance measures play an important role to take a decision regarding alternatives. In this paper...

Attribute reduction (also called feature subset selection) plays an important role in rough set theory. Different from the classical attribute reduction algorithms, the methods of attribute reduction based on covering rough sets appear to be suitable for numerical data. However, it is time-consuming in dealing with the large-scale data. In this paper, we study the problem of attribute reduction...

the rapid growing of information technology (it) motivates and makes competitive advantages in health care industry. nowadays, many hospitals try to build a successful customer relationship management (crm) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. many hospitals have large data warehouses containing customer ...

A novel ranking method based on multi-time information fusion is proposed for intuitionistic fuzzy sets (IFSs) and applied to the threat assessment problem, a multi-attribute decision making (MADM) one. This method integrates a designed intuitionistic fuzzy entropy (IFE), the closeness degree of technique for order preference by similarity to ideal solution (TOPSIS), the decision maker¡¯s (DM¡¯...

This paper proposes a method for ranking decision making units (DMUs) using some of the multiple criteria decision making / multiple attribute decision making          (MCDM /MADM) techniques, namely, interval analytic hierarchy process (IAHP)          and the technique for order preference by similarity to an ideal solution (TOPSIS).          Since the efficiency score of unity is assigned to ...

Across 4,151 participants, the authors demonstrate a novel framing effect, attribute matching, whereby matching a salient attribute of a decision frame with that of a decision's options facilitates decision-making. This attribute matching is shown to increase decision confidence and, ultimately, consensus estimates by increasing feelings of metacognitive ease. In Study 1, participants choosing ...