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Scientific Research Publishing11d
Wilson, D.L. (1994) The Analysis of Survival (Mortality) Data: Fitting Gompertz, Weibull, and Logistic Functions. Mechanisms of Ageing and Development, 74, 15-33.
ABSTRACT: Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional health data characterized by ordinal outcomes. This study offers a comparative ...
ascopubs.org21d
How To Build and Interpret a Nomogram for Cancer Prognosis
Models discussed thus far assume that the relationship between a given factor and the outcome follows a linear function (the logistic model assumes a linear relationship on the logit scale and the Cox ...
Scientific Research Publishing11d
Larasati, A., DeYong, C. and Slevitch, L. (2011) Comparing Neural Network and Ordinal Logistic Regression to Analyze Attitude Responses. Service Science, 3, 304-312.
ABSTRACT: Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional health data characterized by ordinal outcomes. This study offers a comparative ...
Hosted on MSN16d
Logistic Regression Cost Function ¦ Machine Learning ¦ Simply Explained
Learn what is Logistic Regression Cost Function in Machine Learning and the interpretation behind it. Logistic Regression Cost function is "error" representation of the model. It shows how the ...
Healio29d
4D-guided CRT lead placement improves left ventricular function vs. standard care
4D model-guided cardiac resynchronization lead placement improved left ventricular function vs. standard care. Quality of life and physical function were not significantly different between the ...
UBS11d
Group Functions careers
From Technology and Compliance to Human Resources and Treasury. Most of our support and control functions are fully shared among the business divisions, where they have full management responsibility.