Updating the 1:50,000 Dutch soil map using legacy soil data: A multinomial logistic regression approach

Geoderma ◽  
2009 ◽  
Vol 151 (3-4) ◽  
pp. 311-326 ◽  
Author(s):  
Bas Kempen ◽  
Dick J. Brus ◽  
Gerard B.M. Heuvelink ◽  
Jetse J. Stoorvogel
Keyword(s):  
Logistic Regression ◽  
Multinomial Logistic Regression ◽  
Soil Map ◽  
Regression Approach

A Multinomial Logistic Regression Approach for Arrhythmia Detection

2017 ◽  
Vol 8 (4) ◽  
pp. 17-33 ◽  
Author(s):  
Omar Behadada ◽  
Marcello Trovati ◽  
Georgios Kontonatsios ◽  
Yannis Korkontzelos
Keyword(s):  
Logistic Regression ◽  
Big Data ◽  
Multinomial Logistic Regression ◽  
Vascular Diseases ◽  
Arrhythmia Detection ◽  
Medical Sector ◽  
The World ◽  
Regression Approach ◽  
Insight Into ◽  
Tools And Methods

Cardiovascular diseases are the leading causes on mortality in the world. Consequently, tools and methods providing useful and applicable insights into their assessment play a crucial role in the prediction and managements of specific heart conditions. In this article, we introduce a method based on multi-class Logistic Regression as a classifier to provide a powerful and accurate insight into cardiac arrhythmia, which is one of the predictors of serious vascular diseases. As suggested by our evaluation, this provides a robust, scalable, and accurate system, which can successfully tackle the challenges posed by the utilisation of big data in the medical sector.

scholarly journals ASSESSMENT OF ABNORMALLY LOW TENDERS: A MULTINOMIAL LOGISTIC REGRESSION APPROACH

2015 ◽  
Vol 23 (6) ◽  
pp. 848-859
Author(s):  
Murat GUNDUZ ◽  
H. Volkan KARACAN
Keyword(s):  
Logistic Regression ◽  
Control Systems ◽  
Multinomial Logistic Regression ◽  
Past Research ◽  
Negative Effects ◽  
Statistical Tool ◽  
Factors Affecting ◽  
Regression Approach ◽  
Negative Impacts ◽  
Significant Factors

This study was performed in order to reveal factors affecting abnormally low tenders (ALTs) and to minimize negative effects of them. A thorough literature review was carried out to observe past research about the reasons of and possible solutions to ALTs. A questionnaire was prepared and submitted to construction professionals to capture negative impacts of ALTs based on the interviews with experts and past literature. 430 companies responded to the questionnaire. The data analysis was carried out by the multinomial logistic regression statistical tool. Having quality control systems and restricted procedure with prequalification procurement systems were main significant factors to reduce ALTs. Based on all significant factors, recommendations were made to construction professionals and companies to reduce adverse effects of ALTs.

scholarly journals MULTINOMIAL LOGISTIC REGRESSION APPROACH FOR THE EVALUATION OF BINARY DIAGNOSTIC TEST IN MEDICAL RESEARCH

2015 ◽  
Vol 16 (2) ◽  
pp. 203-222 ◽  
Author(s):  
Alok Kumar Dwivedi ◽  
Indika Mallawaarachchi ◽  
Juan B. Figueroa-Casas ◽  
Angel M. Morales ◽  
Patrick Tarwater
Keyword(s):  
Logistic Regression ◽  
Medical Research ◽  
Diagnostic Test ◽  
Multinomial Logistic Regression ◽  
Regression Approach
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