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We propose a novel adaptive penalized logistic regression modeling strategy based on Wilcoxon rank sum test (WRST) to effectively uncover driver genes in classification. In order to incorporate significance of gene in classification, we first measure significance of each gene by gene ranking method based on WRST, and then the adaptive L $_{1}$<alternatives> <inline-graphic xlink:href="park-ieq1-2561937.gif"/></alternatives>...
Interval-valued data arise in practical situations such as recording monthly interval temperatures at meteorological stations, daily interval stock prices, etc. This paper introduces a multinomial logistic regression method for interval-valued data in order to classify items described by interval-valued variables into a pre-defined number of a priori classes. Applications of the proposed approach...
In large organizations and small firms in transportation, there is a growing need to use and analyze spatial data. Transportation system analysis and planning as well as mobility studies frequently use Geographic Information Systems (GIS). In this paper we propose the development of a web services platform dedicated to transportation and logistics. Taking advantage of the web services development...
Ensemble learning aims to improve generalization ability by using multiple base learners. It is well-known that to construct a good ensemble, the base learners should be accurate as well as diverse. In this paper, unlabeled data is exploited to facilitate ensemble learning by helping augment the diversity among the base learners. Specifically, a semi-supervised ensemble method named UDEED is proposed...
Cluster analysis is one of the most important functions of data mining. Expectation Maximization (EM) method is an important technology based on model clustering method. The expectation maximization algorithm is analyzed in this research and applied to Adaptive Testing System, in which logistic function in item response theory serves as a model, and the combination of methods of marginal maximum likelihood...
In the domain of logistics, Radio Frequency Identification (RFID) promises a plethora of benefits due to an enhanced efficiency, accuracy, and preciseness of object identification. Many of the far-reaching solutions proposed in the literature are based on data exchange, integration, and analysis. However, the respective applications have so far not been thoroughly scrutinized regarding relevance and...
In an association study, empirical evidences support the commonality of gene-gene interactions. Although genetic factors play an important role in many human diseases, multiple genes or genes and environmental factors may ultimately influence individual risk for these disease. However, such interactions are difficult to detect. In this paper, we propose a penalized area under ROC curve (AUC) maximization...
Statistical models in which both fixed and random effects enter nonlinearly are becoming increasingly popular. These models have a wide variety of applications in many areas such as agriculture, forestry, biology, ecology, biomedicine, sociology, economics, pharmacokinetics, and other areas. Mixed effect models are flexible models to analyze grouped data including longitudinal data, repeated measures...
Classifiers based on parametric or non-parametric learning methods have different advantages and disadvantages. To take advantage of the strengths of both methods, we propose an algorithm that combines a parametric model (logistic regression) with a non-parametric classification method (k-nearest neighbors). This combination is based on a measure of appropriateness that uses a heuristic to decide...
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