Motivation: Interpretation of classification models derived from gene expression data is usually not simple, yet it is an important aspect in the analytical process. We investigate the performance of small rule-based classifiers based on fuzzy logic in five data sets that are different in size, laboratory origin, and biomedical domain. Results: The classifiers resulted in rules that can be read...

The purpose of this study was to evaluate the ability of fuzzy neural network model to predict the likelihood of coronary heart disease for individuals based on knowledge of their biomarkers, risk habits and demographic profiles. The prediction performance of fuzzy neural network models were measured in terms of percentage accuracies and compared with the prediction performance of logistic regr...

In the context of polytomous regression, as with any generalized linear model, robustness issues are well documented. Existing robust estimators designed to protect against misclassification, but do not outlying covariates. It is shown that this can have a much bigger impact on estimation and testing than misclassification alone. To address problem, two new introduced: model-type estimator an o...

caesarean section (c-section) rates have been increasing dramatically in the past decades around the world. this increase has been attributed to multiple factors such as maternal, socio-demographic and institutional fac-tors. therefore, this study examines the impact of maternal, socio-demographic and relevant characteristics on caesar-ean delivery in the northern region of bangladesh.this stud...

چکیده شناسایی رقومی خاک ها بهعنوان ابزاری برای ایجاد اطلاعات مکانی خاک، راه حل هایی برای نیاز رو به افزایش نقشه های خاک با تفکیک مکانی بالا را تأمین می کند. بنابراین، باید روش های جدید بهمنظور بهدست آوردن اطلاعات مکانی خاک با تفکیک مکانی بالا توسعه پیدا کند. به همین منظور مطالعه ای جهت پیش بینی کلاس های خاک با استفاده از مدل های رگرسیونی در منطقه زرند کرمان طراحی گردید. در این مطالعه، مدل های ر...