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...

Abstract Aiming at the defects of difficult to establish fault diagnosis models caused by small scale liquid rocket engine test data, imbalanced categories and high coupling, platform with 10 are developed for diagnosis, covering K-nearest neighbor (KNN) model, optimized KNN logistic regression (LR) LR support vector machine K-means decision tree neural network random forest model light-GBM mod...

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...

This study analyses the relationship between meteorological phenomena and outbreaks of waterborne-transmitted vero cytotoxin-producing Escherichia coli (VTEC) in the Republic of Ireland over an 8-year period (2005-2012). Data pertaining to the notification of waterborne VTEC outbreaks were extracted from the Computerised Infectious Disease Reporting system, which is administered through the nat...

In recent years, several authors have described a hybrid discriminative-generative model for classification. In this paper we examine construction of such hybrid models from data where we use logistic regression (LR) as a discriminative component, and naı̈ve Bayes (NB) as a generative component. First, we estimate a Markov blanket of the class variable to reduce the set of features. Next, we use...

Breast cancer is the most common malignant tumor found in women, and there no cure for advanced breast cancer. Early detection treatment can effectively improve patient survival. This paper uses five machine learning classification models, namely Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), K-Nearest Neighbors Algorithm (KNN). The training data...

logistic regression (lr) was used to model urban growth between the years 1987 and 2001 in gorgan city, north east of iran. three groups of variables including economic-social, land use and biophysical variables were used in the modeling practice. using covariance of the independent variables, distance to administrative and sporting centers plus distance to cities were removed. roc (relative op...

BACKGROUND Dyslipidemia is an extremely prevalent but preventable risk factor for cardiovascular disease. However, many dyslipidemia patients remain undetected in resource limited settings. The study was performed to develop and evaluate a simple and effective prediction approach without biochemical parameters to identify those at high risk of dyslipidemia in rural adult population. METHODS D...