… a heterogeneous ensemble learning approach for predicting neuroblastoma patient
survival and extracting decision rules to aid clinical decisionmaking. A heterogeneous feature …

… The Reynolds stress and the time-mean strain tensors have been computed from data, in
order to adopt the SBL-Bayesian LASSO from a large library of candidate predictors based on …

… Risk stratification and therapy decision making is … LASSO 6. Whereas the frequentist
perception of regularization assumes the shrinkage parameter fixed, the Bayesian LASSO allows to …

… regression to a Bayesian setting. Then, we propose a modified group Lasso for categorical
factor … Econometrically speaking, the Tobit model assumes a so-called single decisionmaking …

… frontiers in Bayesian inference and decision making. The … in shaping the recent expansion
of Bayesian research. Jim’s … Bayesian-frequentist interface. This interest led him to study …

… the Bayesian information criterion, LASSO … decision-making tools with a good discriminative
ability and to our understanding of risk factors for DR. This study supports that LASSO can …

… based retrospective Bayesian Lasso … Bayesian Lasso scheme that examines both trio data
and case/control data simultaneously. We call our method combined Logistic Bayesian Lasso …

… Likewise, we present a hybrid model that combines lasso and ridge regression methods for
… Naive Bayes classification algorithm prioritizes dataset preprocessing utilizing Naïve Bayes …

… Therefore, this paper evaluates the performance of the Partially Protected Bayesian LASSO
… two Bayesian LASSO models were small, the results show that the regular Bayesian LASSO …