This study examined the predictive power of data mining algorithms by comparing the performance of a logistic regression algorithm with that of a decision tree algorithm called CHAID (Chi-squared Automatic Interaction Detection). Unlike in the previous studies, the decision tree performed better than logistic regression. This paper also demonstrated how another data mining model, called associa...

In this paper we present a study that suggests a two-step approach, called the Iterative Refinement Algorithm (IRA), for improving the classification accuracy of inductive learning algorithms applied to very large datasets. We present the preliminary test results for IRA compared to other prediction methods including logistic regression, discriminant analysis, neural networks, C5, CART, and CHA...

Abstract The main purpose of this study is to investigate the best predictor firm performance among different proxies. A sample 287 Czech firms was taken from automobile, construction, and manufacturing sectors. Panel data acquired Albertina database for time period 2016 2020. Three proxies performance, return assets (RoA), equity (RoE), capital employed (RoCE) were used as dependent variables....

Amaç: Bu araştırmanın amacı hemşirelik öğrencilerinin intramüsküler enjeksiyona ilişkin bilgi düzeylerini yordayan bazı değişkenlerin incelenmesidir. Gereç ve Yöntem: Tanımlayıcı kesitsel tipteki bu araştırma 1 Aralık 2020-15 Ocak 2021 tarihleri arasında araştırmaya katılmayı gönüllü olarak kabul eden 359 öğrencisi ile yürütüldü. Araştırma verileri ''Öğrenci Bilgi Formu'' ''IM Enjeksiyon Başarı...

BACKGROUND AND OBJECTIVES Iron overload used to be considered rare among hemodialysis patients after the advent of erythropoesis-stimulating agents, but recent MRI studies have challenged this view. The aim of this study, based on decision-tree learning and on MRI determination of hepatic iron content, was to identify a noxious pattern of parenteral iron administration in hemodialysis patients....