56 resultados para Multivariate Adaptive Regression Splines (MARS)
Resumo:
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.
Resumo:
Coastal wetlands are dynamic and include the freshwater-intertidal interface. In many parts of the world such wetlands are under pressure from increasing human populations and from predicted sea-level rise. Their complexity and the limited knowledge of processes operating in these systems combine to make them a management challenge.Adaptive management is advocated for complex ecosystem management (Hackney 2000; Meretsky et al. 2000; Thom 2000;National Research Council 2003).Adaptive management identifies management aims,makes an inventory/environmental assessment,plans management actions, implements these, assesses outcomes, and provides feedback to iterate the process (Holling 1978;Walters and Holling 1990). This allows for a dynamic management system that is responsive to change. In the area of wetland management recent adaptive approaches are exemplified by Natuhara et al. (2004) for wild bird management, Bunch and Dudycha (2004) for a river system, Thom (2000) for restoration, and Quinn and Hanna (2003) for seasonal wetlands in California. There are many wetland habitats for which we currently have only rudimentary knowledge (Hackney 2000), emphasizing the need for good information as a prerequisite for effective management. The management framework must also provide a way to incorporate the best available science into management decisions and to use management outcomes as opportunities to improve scientific understanding and provide feedback to the decision system. Figure 9.1 shows a model developed by Anorov (2004) based on the process-response model of Maltby et al. (1994) that forms a framework for the science that underlies an adaptive management system in the wetland context.
Resumo:
A mixture model incorporating long-term survivors has been adopted in the field of biostatistics where some individuals may never experience the failure event under study. The surviving fractions may be considered as cured. In most applications, the survival times are assumed to be independent. However, when the survival data are obtained from a multi-centre clinical trial, it is conceived that the environ mental conditions and facilities shared within clinic affects the proportion cured as well as the failure risk for the uncured individuals. It necessitates a long-term survivor mixture model with random effects. In this paper, the long-term survivor mixture model is extended for the analysis of multivariate failure time data using the generalized linear mixed model (GLMM) approach. The proposed model is applied to analyse a numerical data set from a multi-centre clinical trial of carcinoma as an illustration. Some simulation experiments are performed to assess the applicability of the model based on the average biases of the estimates formed. Copyright (C) 2001 John Wiley & Sons, Ltd.
Resumo:
Purpose: To determine whether constriction of proximal arterial vessels precedes involution of the distal hyaloid vasculature in the mouse, under normal conditions, and whether this vasoconstriction is less pronounced when the distal hyaloid network persists, as it does in oxygen-induced retinopathy (OIR). Methods: Photomicrographs of the vasa hyaloidea propria were analysed from pre-term pups (1-2 days prior to birth), and on Days 1-11 post-birth. The OIR model involved exposing pups to similar to 90% O-2 from D1-5, followed by return to ambient air. At sampling times pups were anaesthetised and perfused with india ink. Retinal flatmounts were also incubated with FITC-lectin (BS-1, G. simplicifolia,); this labels all vessels, allowing identification of vessels not patent to the perfusate. Results: Mean diameter of proximal hyaloid vessels in preterm pups was 25.44 +/- 1.98 mum; +/-1 SEM). Within 3-12 hrs of birth, significant vasoconstriction was evident (diameter:12.45 +/- 0.88 mum), and normal hyaloid regression subsequently occurred. Similar vasoconstriction occurred in the O-2-treated group, but this was reversed upon return to room air, with significant dilation of proximal vessels by D7 (diameter: 31.75 +/- 11.99 mum) and distal hyaloid vessels subsequently became enlarged and tortuous. Conclusions: Under normal conditions, vasoconstriction of proximal hyaloid vessels occurs at birth, preceding attenuation of distal hyaloid vessels. Vasoconstriction also occurs in O-2-treated pups during treatment, but upon return to room air, the remaining hyaloid vessels dilate proximally, and the distal vessels become dilated and tortuous. These observations support the contention that regression of the hyaloid network is dependent, in the first instance, on proximal arterial vasoconstriction.
Resumo:
This paper proposed a novel model for short term load forecast in the competitive electricity market. The prior electricity demand data are treated as time series. The forecast model is based on wavelet multi-resolution decomposition by autocorrelation shell representation and neural networks (multilayer perceptrons, or MLPs) modeling of wavelet coefficients. To minimize the influence of noisy low level coefficients, we applied the practical Bayesian method Automatic Relevance Determination (ARD) model to choose the size of MLPs, which are then trained to provide forecasts. The individual wavelet domain forecasts are recombined to form the accurate overall forecast. The proposed method is tested using Queensland electricity demand data from the Australian National Electricity Market. (C) 2001 Elsevier Science B.V. All rights reserved.
Resumo:
OBJECTIVES: The authors prospectively examined the association between bowel movement frequency (used as a proxy for intestinal transit), laxative use, and the risk of symptomatic gallstone disease. METHODS: A total of 79,829 women, aged 36–61 yr, without a history of symptomatic gallstone disease and free of cancer, responded to a mailed questionnaire in 1982 that assessed bowel movement frequency and use of laxatives. Between 1984 and 1996, 4,443 incident cases of symptomatic gallstone disease were documented. Relative risks (RRs) of symptomatic gallstone disease and 95% confidence intervals (CIs) were calculated using logistic regression. RESULTS: After controlling for age and established risk factors, the multivariate RRs were, compared to women with daily bowel movements, 0.97 (95% CI 0.86–1.08) for women with bowel movements every third day or less, and 1.00 (95% CI 0.91–1.11) for women with bowel movement more than once daily. No trend was evident. As compared to women who never used laxatives in 1982, a significant modest inverse association was seen for monthly laxative use, with a multivariate RR of 0.84 (95% CI 0.72–0.98), and weekly to daily laxative use was associated with a RR of 0.88 (95% CI 0.78–1.02). CONCLUSIONS: These findings do not support an association between infrequent bowel movements and risk of symptomatic gallstone disease in women, and indicate that simple questions directed at bowel movement frequency are unlikely to enhance our ability to predict risk of symptomatic gallstone disease. The slightly inverse association between use of laxatives and risk of symptomatic gallstone disease may be due to a mechanism that is not related to bowel movement frequency.
Resumo:
Adaptive changes that occur after chronic exposure to ethanol are an important component in the development of physical dependence. We have focused our research on ethanol-induced changes in the expression of several genes that may be important in adaptation. In this article, we describe adaptive changes at the level of the N-methyl-D-aspartate receptor, in the protein expression and activity of the Egr transcription factors, and in the expression of a novel gene of unknown function. (C) 2001 Elsevier Science Inc. All rights reserved.
Resumo:
It is not possible to make measurements of the phase of an optical mode using linear optics without introducing an extra phase uncertainty. This extra phase variance is quite large for heterodyne measurements, however it is possible to reduce it to the theoretical limit of log (n) over bar (4 (n) over bar (2)) using adaptive measurements. These measurements are quite sensitive to experimental inaccuracies, especially time delays and inefficient detectors. Here it is shown that the minimum introduced phase variance when there is a time delay of tau is tau/(8 (n) over bar). This result is verified numerically, showing that the phase variance introduced approaches this limit for most of the adaptive schemes using the best final phase estimate. The main exception is the adaptive mark II scheme with simplified feedback, which is extremely sensitive to time delays. The extra phase variance due to time delays is considered for the mark I case with simplified feedback, verifying the tau /2 result obtained by Wiseman and Killip both by a more rigorous analytic technique and numerically.
Resumo:
Objective: We examined the relationship between self-reported calcium (Cal intake and bone mineral content (BMC) in children and adolescents. We hypothesized that an expression of Ca adjusted for energy intake (El), i.e., Ca density, would be a better predictor of BMC than unadjusted Ca because of underreporting of EI. Methods: Data were obtained on dietary intakes (repeated 24-hour recalls) and BMC (by DEXA) in a cross-section of 227 children aged 8 to 17 years. Bivariate and multivariate analyses were used to examine die relationship between Ca, Ca density, and the dependent variables total body BMC and lumbar spine BMC. Covariates included were height, weight, bone area, maturity age, activity score and El. Results: Reported El compared to estimated basal metabolic rate suggested underreporting of El. Total body and lumbar spine BMC were significantly associated with El, but not Ca or Ca density, in bivariate analyses. After controlling for size and maturity, multiple linear regression analysis revealed unadjusted Ca to be a predictor of BMC in males in the total body (p = 0.08) and lumbar spine (p = 0.01). Unadjusted Ca was not a predictor of BMC at either site in females. Ca density was not a better predictor of BMC at either site in males or females. Conclusions: The relationship observed in male adolescents in this study between Ca intake and BMC is similar to that seen in clinical trials. Ca density did not enable us to see a relationship between Ca intake and BMC in females, which may reflect systematic reporting errors or that diet is not a limiting factor in this group of healthy adolescents.