We compare Bayes Model Averaging, BMA, to a non-Bayes form of model averaging called stacking. In stacking, the weights are no longer posterior probabilities of models; they are obtained by a technique based on cross-validation. When the correct data generating model (DGM) is on the list of models under consideration BMA is never worse than stacking and often is demonstrably better, provided th...

Although Bayesian model averaging (BMA) is in principle the optimal method for combining learned models, it has received relatively little attention in the machine learning literature. This article describes an extensive empirical study of the application of BMA to rule induction. BMA is applied to a variety of tasks and compared with more ad hoc alternatives like bagging. In each case, BMA typ...

Trephine biopsy (TB) combined with bone marrow aspiration (BMA) is the most common method for evaluating bone marrow (BM) involvement in non-Hodgkin's lymphomas. Nevertheless, the role of TB in high-grade lymphomas remains controversial. We reviewed the results of 42 consecutive BMAs and TBs performed simultaneously in 29 patients with lymphoblastic lymphoma (LL) and small, non-cleaved cell lym...

Unlike white and brown adipose tissues, the bone marrow adipocyte (BMA) exists in a microenvironment containing unique populations of hematopoietic and skeletal cells. To study this microenvironment at the sub-cellular level, we performed a three-dimensional analysis of the ultrastructure of the BMA niche with focused ion beam scanning electron microscopy (FIB-SEM). This revealed that BMAs disp...