Recent work in supervised learning has shown that a surprisingly simple Bayesian classiier with strong assumptions of independence among features, called naive Bayes, is competitive with state-of-the-art classiiers such as C4.5. This fact raises the question of whether a classiier with less restrictive assumptions can perform even better. In this paper we evaluate approaches for inducing classi...

In the mouse blastocyst, epiblast cells are newly formed shortly before implantation. They possess a unique developmental plasticity, termed naive pluripotency. For development to proceed, this naive state must be subsumed by multi-lineage differentiation within 72 h following implantation. In vitro differentiation of naive embryonic stem cells (ESCs) cultured in controlled conditions provides ...

Many immunological defects have been described in HIV disease, including a diminished capacity of naive CD4+ T cells to expand after TCR stimulation. The mechanisms underlying impaired naive CD4+ T cell expansion in HIV disease are not well described. Using a rigorous phenotypic definition of naive T cells, we found that cell cycle entry after TCR engagement was restricted to cells that increas...

The authors investigated the occurrence of naive chimpanzees' (Pan troglodytes) spontaneous observation of experienced conspecifics during a tool-use task entailing honey fishing. The chimpanzees were presented with 20 kinds of "tools" of which 12 kinds were usable. Six pairs of naive and experienced chimpanzees were brought to this honey-fishing situation. A total of 40 observation episodes oc...

It is well-known that naive Bayes performs surprisingly well in classification, but its probability estimation is poor. In many applications, however, a ranking based on class probabilities is desired. For example, a ranking of customers in terms of the likelihood that they buy one’s products is useful in direct marketing. What is the general performance of naive Bayes in ranking? In this paper...

In this paper, the naive credal classifier, which is a set-valued counterpart of naive Bayes, is extended to a general and flexible treatment of incomplete data, yielding a new classifier called naive credal classifier 2 (NCC2). The new classifier delivers classifications that are reliable even in the presence of small sample sizes and missing values. Extensive empirical evaluations show that, ...

The naive Bayes classifier continues to be a popular learning algorithm for data mining applications due to its simplicity and linear run-time. Many enhancements to the basic algorithm have been proposed to help mitigate its primary weakness—the assumption that attributes are independent given the class. All of them improve the performance of naive Bayes at the expense (to a greater or lesser d...

Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competitive with state of the art classifiers such as C4.5. This fact raises the question of whether a classifier with less restrictive assumptions can perform even better. In this paper we examine and evaluate approaches for ...

In studies of immune aging, naive T cells frequently take center stage. Describing the complexity of the human naive T cell repertoire remains a daunting task; however, emerging data suggest that homeostatic mechanisms are robust enough to maintain a large and diverse CD4 T cell repertoire with age. Compartment shrinkage and clonal expansions are challenges for naive CD8 T cells. In addition to...