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Showing 1 to 3 of 3 for “"Penalized logistic regression"”.
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High-dimensional classification and attribute-based forecasting
… genes is much larger than the sample size. The penalized logistic regression method is known for simultaneous variable selection and classification. However, the performance of this method declines as the number of variables increases. With this concern, in the first study, we propose a new …
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An Application of Variable Selection Methods to Identify Influential Factors of ADHD Diagnosis in Children
… in uence ADHD diagnosis in children using penalized logistic regression. According to the CDC about 11% of United States children between the ages of 4 and 17 are diagnosed with ADHD. It is important that children are correctly diagnosed. This thesis will help identify which factors are …
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Bayesian variable selection in high dimensional censored regression models
… selection problem in a high-dimensional censored regression model that can handle gene expression data with hundreds of thousands of features. We propose an EM-like iterative algorithm for accelerated failure models (AFT models) with censored survival data under no distributional assumption. …