Logistic regression analysis was performed to determine risk factors for RVO.Of the 1775 subjects examined, 38 had RVO. The prevalence of RVO was 2.1% ... M Yasuda,Y Kiyohara,S Arakawa,... - 《Investigative Ophthalmology & Visual Science》 被引量: 93发表: 2010年 Vitrectomy for Diabetic Mac...
Lemeshow S, Hosmer DW., Jr Logistic Regression Analysis: Applications to Ophthalmic Research. Am J of Ophthalmol. 2009; 147 (5):766–767.Lemeshow S, Hosmer DW. Logistic regression analysis: applications to ophthalmic research. Am J Ophthalmol 2009;147:766 -767....
Applied Logistic Regression Analysis (Quantitative Applications in the Social Sciences)The focus in this is again on logistic regression models for individual level data, but aggregate or grouped data are also considered. The book includes detailed discussions of goodness of fit, indices of predictive ...
摘要: Regression modeling strategies : with applications to linear models, logistic regression, and survival analysis Frank E. Harrell, Jr (Springer series in statistics) Springer, c2010 : [pbk.]出版时间: 2010 ISBN: 9781441929181 被引量: 368 ...
Simultaneous confidence bands for log-logistic regression with applications in risk assessment In risk assessment, it is often desired to make inferences on the low dose levels at which a specific benchmark risk is attained. Applications of simultane... LL Model,B Dose,R Assessment,... 被引量...
Logistic regression (LR) is widely applied as a powerful classification method in various fields, and a variety of optimization methods have been developed. To cope with large-scale problems, an efficient optimization method for LR is required in terms of computational cost and memory usage. In ...
Logistic regression: An estimate of an event occurring, usually a binary classification such as a yes or no answer. Decision trees: A series of yes/no, if/else, or other binary results placed into a visualization known as a decision tree. ...
In this paper we consider a label-noise robust version of the logistic regression and multinomial logistic regression classifiers and develop the following contributions: (i) We derive efficient multiplicative updates to estimate the label flipping probabilities, and we give a proof of convergence for ...
The tree-based algorithms, Random Forest (RF) and Decision Tree (DT), were clearly superior to Logistic Regression (LR) and Support Vector Machine (SVM), because of unbalanced low sensitivities versus high specificities of the latter methods. Furthermore, RF exhibited better prediction than DT ...
Several machine learning algorithms, such as decision trees, logistic regression, and random forest, are already being used for this purpose. Data science also allows administrators toanalyzethe activities and teaching methods of teachers. It provides valuable information that shows the strengths and we...