Penalized discriminant analysis of [/sup 15/O]-water PET brain images with prediction error selection of smoothness and regularization hyperparameters

2001 ◽  
Vol 20 (5) ◽  
pp. 376-387 ◽  
Author(s):  
R. Kustra ◽  
S. Strother
Keyword(s):  
Discriminant Analysis ◽  
Prediction Error ◽  
Brain Images ◽  
Penalized Discriminant Analysis ◽  
Selection Of

Segmentation of [11C]DASB and [carbonyl-11C]WAY-100635 PET brain images using linear discriminant analysis

NeuroImage ◽  
2010 ◽  
Vol 52 ◽  
pp. S155-S156 ◽  
Author(s):  
Andreas Hahn ◽  
Markus Savli ◽  
Christoph Spindelegger ◽  
Daniela Häusler ◽  
Wolfgang Wadsak ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Brain Images ◽  
Linear Discriminant ◽  
Way 100635

Segmentation of magnetic resonance brain images through discriminant analysis

2003 ◽  
Vol 131 (1-2) ◽  
pp. 65-74 ◽  
Author(s):  
Umberto Amato ◽  
Michele Larobina ◽  
Anestis Antoniadis ◽  
Bruno Alfano
Keyword(s):  
Discriminant Analysis ◽  
Magnetic Resonance ◽  
Brain Images

scholarly journals Clients’ selection of auditors: evidence from the Athens stock exchange

2015 ◽  
Vol 3 (2) ◽  
pp. 156
Author(s):  
Anastasia Maggina
Keyword(s):  
Logistic Regression ◽  
Discriminant Analysis ◽  
Stock Exchange ◽  
Audit Fees ◽  
Statistical Technique ◽  
Financial Ratios ◽  
Institutional Factors ◽  
Data Set ◽  
Second Tier ◽  
Selection Of

<p>The auditing profession is at a crossroad worldwide. It currently faces many challenges especially in Greece where auditor rotation has been instituted as mandatory by EU regulation and the auditing profession is going to be fully liberalized (no limits on audit fees) . Given the Greek environment, it is important to investigate how client companies select auditors. In this study we address three questions. First, can selection of auditors be forecasted? Second, which statistical technique better fits the data set? Third, are there differences in firms’ financial ratios as well as institutional factors that affect auditor choice? Clients’ selection of auditors is considered in a research context using discriminant analysis and logistic regression. The discriminating factors between the two groups of companies include some firm financial ratios and institutional factors: QATA(Quick Assets/Total Assets) when using one year data, and QATA(Quick Assets/Total Assets) and SHAREHOLD (level of shareholdings) when using two year data. Prediction accuracy is close to 60.0 percent using discriminant analysis and around 80.0 percent using logistic regression. The contribution of this study is that it discriminates between the two groups of companies (Big Four versus second-tier or local auditing firms) in an IFRS environment.</p>

Genetic algorithm for feature selection of MR brain images using wavelet co-occurence

2011 ◽  
Author(s):  
Ahmed Kharrat ◽  
Nacéra Benamrane ◽  
Mohamed B. Messaoud ◽  
Mohamed Abid
Keyword(s):  
Genetic Algorithm ◽  
Feature Selection ◽  
Brain Images ◽  
Mr Brain Images ◽  
Mr Brain ◽  
Selection Of
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