961 resultados para Set covering theory


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Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.

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Objective. To validate a core set of outcome measures for the evaluation of response to treatment in patients with juvenile dermatomyositis (DM). Methods. In 2001, a preliminary consensus-derived core set for evaluating response to therapy in juvenile DM was established. In the present study, the core set was validated through an evidence-based, large-scale data collection that led to the enrollment of 294 patients from 36 countries. Consecutive patients with active disease were assessed at baseline and after 6 months. The validation procedures included assessment of feasibility, responsiveness, discriminant and construct ability, concordce in the evaluation of response to therapy between physicians and parents, redundancy, internal consistency, and ability to predict a therapeutic response. Results. The following clinical measures were found to be feasible, and to have good construct validity, discriminative ability, and internal consistency; furthermore, they were not redundant, proved responsive to clinically important changes in disease activity, and were associated strongly with treatment outcome and thus were included in the final core set: 1) physician`s global assessment of disease activity, 2) muscle strength, 3) global disease activity measure, 4) parent`s global assessment of patient`s well-being, 5) functional ability, and 6) health-related quality of life. Conclusion. The members of the Paediatric Rheumatology International Trials Organisation, with the endorsement of the American College of Rheumatology and the European Leauge Against Rheumatism, propose a core set of criteria for the evaluation of response of therapy that is scientifically and clinically relevant and statistically validated. The core set will help standardize the conduct and reporting of clinical trials and assist practitioners in deciding whether a child with juvenile DM has responded adequately to therapy.