Improving Portfolio Performance Using Attribute Selection and Combination

Author(s):  
Xiaoran Wang ◽  
James Ho-Shek ◽  
Dominik Ondusko ◽  
D. Frank Hsu
1989 ◽  
Vol 28 (02) ◽  
pp. 69-77 ◽  
Author(s):  
R. Haux

Abstract:Expert systems in medicine are frequently restricted to assisting the physician to derive a patient-specific diagnosis and therapy proposal. In many cases, however, there is a clinical need to use these patient data for other purposes as well. The intention of this paper is to show how and to what extent patient data in expert systems can additionally be used to create clinical registries and for statistical data analysis. At first, the pitfalls of goal-oriented mechanisms for the multiple usability of data are shown by means of an example. Then a data acquisition and inference mechanism is proposed, which includes a procedure for controlling selection bias, the so-called knowledge-based attribute selection. The functional view and the architectural view of expert systems suitable for the multiple usability of patient data is outlined in general and then by means of an application example. Finally, the ideas presented are discussed and compared with related approaches.


2019 ◽  
Vol 18 (1) ◽  
pp. 35-55
Author(s):  
Mohammad Aizat Basir ◽  
Yuhanis Yusof ◽  
Mohamed Saifullah Hussin

2019 ◽  
Author(s):  
Edward Trevillion ◽  
Colin Jones ◽  
Alan Gardner ◽  
Stewart Cowe

CFA Digest ◽  
2001 ◽  
Vol 31 (1) ◽  
pp. 83-84
Author(s):  
Daren E. Miller

1966 ◽  
Vol 22 (1) ◽  
pp. 106-108
Author(s):  
John C. Sherman

Author(s):  
Mustafa S. Abd ◽  
Suhad Faisal Behadili

Psychological research centers help indirectly contact professionals from the fields of human life, job environment, family life, and psychological infrastructure for psychiatric patients. This research aims to detect job apathy patterns from the behavior of employee groups in the University of Baghdad and the Iraqi Ministry of Higher Education and Scientific Research. This investigation presents an approach using data mining techniques to acquire new knowledge and differs from statistical studies in terms of supporting the researchers’ evolving needs. These techniques manipulate redundant or irrelevant attributes to discover interesting patterns. The principal issue identifies several important and affective questions taken from a questionnaire, and the psychiatric researchers recommend these questions. Useless questions are pruned using the attribute selection method. Moreover, pieces of information gained through these questions are measured according to a specific class and ranked accordingly. Association and a priori algorithms are used to detect the most influential and interrelated questions in the questionnaire. Consequently, the decisive parameters that may lead to job apathy are determined.


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