… influence on the real estate price are excluded. The grid search algorithm is used to optimize
the model. … Pelckmans,Machine learning approaches to survival analysis:case studies in …

… influence of uncertainty on risk assessment result is not taken into consideration.To overcome
these limitations,the Bayesian … Bayesian risk analysis network models of dam overtopping …

… This study is based on the database of 335 cases which is extracted from one of the …
Bayesian Classifier(TAN)model,Decision Tree(DT)model and K Nearest Neighbors(KNN) model to …

… ENMTools is a set of comparative similarity measures and statistical tests that permit
quantitative comparison of ENMs. It can be used to measure niche overlap among species …

… In such cases, mechanical models and evaluation systems designed for the … case the inrush
will be difficult to control and cause great harm. Therefore, establishing a mechanical model …

… Some of the other tests were done when natural dusk came later in the day. Mating events
… Bayesian clustering analysis assumed that all 15 populations were divided into 2 different …

… diagnostic accuracy, which has been widely used in tumor staging, cancer detection, survival
analysis … The application and research progress of machine learning in radiomics analysis …

… diagnostic prediction models based on three machine learning algorithms and compare the
value of the three models in the diagnosis of … 463 cases of prostate cancer and 493 cases of …

… influenced by inoculation, culture time and their interactions, except for CAT, which was
not influenced by … EBSeq: an empirical Bayes hierarchical model for inference in RNA-seq …

… Asterisks indicate Bayesian posterior probabilities (BPP) ≥95% and bootstrap values (BS)
≥70% in our maximum likelihood analysis and maximum parsimony analyses. Relationships …