Use of probabilistic information by mock civil juries

A Bayesian model that provides probabilistic information about the spread of malignancy in a Hodgkin’s disease patient has been developed at the Tufts New England Medical Center. In assessing the model’s reliability, it seemed important to use it to make predictions about patients other than those relevant to its construction. The accuracy of these predictions could then be tested statistically. This paper describes such a test, based on 243 Hodgkin’s disease patients of known pathologic stage. The results obtained were supportive of the model, and the test procedure might interest those wishing to determine whether the imperfections that attend any attempt to make probabilistic forecasts have gravely damaged their accuracy.

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A combination of expert opinion approach to probabilistic information retrieval, part 1: The conceptual model

Information Processing & Management ◽

10.1016/0306-4573(90)90097-l ◽

1990 ◽

Vol 26 (3) ◽

pp. 371-382 ◽

Cited By ~ 32

Author(s):

Paul Thompson

Keyword(s):

Information Retrieval ◽

Conceptual Model ◽

Expert Opinion ◽

Probabilistic Information

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Probabilistic Information Loss Measures in Confidentiality Protection of Continuous Microdata

Data Mining and Knowledge Discovery ◽

10.1007/s10618-005-0011-9 ◽

2005 ◽

Vol 11 (2) ◽

pp. 181-193 ◽

Cited By ~ 56

Author(s):

Josep M. Mateo-Sanz ◽

Josep Domingo-Ferrer ◽

Francesc Sebé

Keyword(s):

Information Loss ◽

Probabilistic Information ◽

Confidentiality Protection

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A neural network for probabilistic information retrieval

Proceedings of the 12th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '89 ◽

10.1145/75334.75338 ◽

1989 ◽

Cited By ~ 24

Author(s):

K. L. Kwok

Keyword(s):

Neural Network ◽

Information Retrieval ◽

Probabilistic Information

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METHODS FOR PROBABILISTIC DECISION MAKING WITH LINGUISTIC INFORMATION

Technological and Economic Development of Economy ◽

10.3846/20294913.2014.869515 ◽

2014 ◽

Vol 20 (2) ◽

pp. 193-209 ◽

Cited By ~ 18

Author(s):

Guiwu Wei ◽

Xiaofei Zhao

Keyword(s):

Decision Making ◽

Weighted Average ◽

Aggregation Operators ◽

Uncertain Information ◽

Owa Operator ◽

Linguistic Information ◽

Probabilistic Information ◽

Ordered Weighted Average ◽

Linguistic Labels ◽

Selection Of

With respect to decision making problems by using probabilities, immediate probabilities and information that can be represented with linguistic labels, some new decision analysis are proposed. Firstly, we shall develop three new aggregation operators: generalized probabilistic 2-tuple weighted average (GP-2TWA) operator, generalized probabilistic 2-tuple ordered weighted average (GP-2TOWA) operator and generalized immediate probabilistic 2-tuple ordered weighted average (GIP-2TOWA) operator. These operators use the weighted average (WA) operator, the ordered weighted average (OWA) operator, linguistic information, probabilistic information and immediate probabilistic information. They are quite useful because they can assess the uncertain information within the problem by using both linguistic labels and the probabilistic information that considers the attitudinal character of the decision maker. In these approaches, alternative appraisal values are calculated by the aggregation of 2-tuple linguistic information. Thus, the ranking of alternative or selection of the most desirable alternative(s) is obtained by the comparison of 2-tuple linguistic information. Finally, we give an illustrative example about selection of strategies to verify the developed approach and to demonstrate its feasibility and practicality.

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