نتایج جستجو برای: logistic and performance
تعداد نتایج: 16954710 فیلتر نتایج به سال:
results the command is addpred for logistic regression models. conclusions the stata package provided herein can encourage the use of novel methods in examining predictive capacity of ever-emerging plethora of novel biomarkers. materials and methods we have written a stata command that is intended to help researchers obtain cut point-free and cut point-based net reclassification improvement ind...
Objective: Nowadays, financial distress prediction is one of the most important research issues in the field of risk management that has always been interesting to banks, companies, corporations, managers and investors. The main objective of this study is to develop a high performance predictive model and to compare the results with other commonly used models in financial distress prediction M...
Background and Objectives : recent years, considerable attention has been paid to statistical models for classification of medical data according to various diseases and their outcomes. Artificial neural networks have been successfully used for pattern recognition and prediction since they are not based on prior assumptions in clinical studies. This study compared two statistical models, arti...
The aim of this study is to prepare the groundwater spring potential map using Weight of Evidence, logistic regression, and frequency ratio methods and comparing their efficiency in Chehlgazi watershed, province of Kurdistan. At first, 17 effective factors in springs occurrence including geology, distance to fault, fault density, elevation, relative permeability of lithological units, slope ste...
In this paper some properties of logistics - x family are discussed and a member of the family, the logistic–normal distribution, is studied in detail. Average deviations, risk function and fashion for logistic–normal distribution is obtained. The method of maximum likelihood estimation is proposed for estimating the parameters of the logistic–normal distribution and a data set is ...
Bivariate semi-logistic and Marshall-Olkin bivariate semi-logistic distributions are introduced. Some properties of these distributions are studied. First order autoregressive processes with bivariate semi-logistic and Marshall-Olkin bivariate semi-logistic distributions as marginals are introduced and studied.
Background: We designed an algorithmic model based on the logistic regression analysis and a non-algorithmic model based on the Artificial Neural Network (ANN). Materials and methods: The ability of these models was compared together in clinical application to differentiate malignant from benign breast tumors in a study group of 161 patients' records. Each patient’s record consisted of 6 subjec...
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