The generation of high-affinity antibodies requires germinal center (GC) development and differentiation of long-lived plasma cells in a multilayered process that is tightly controlled by the activity of multiple transcription factors. Here, we reveal a new layer of complexity by demonstrating that dynamic changes in Id3 and E-protein activity govern both GC and plasma cell differentiation. We ...

Genetic relationships between 22 spring viraemia of carp virus (SVCV) isolates from Austria collected between 1994 and 2007 were determined based on the partial nucleotide sequence of the glycoprotein gene (G gene). Phylogenetic analyses located all Austrian isolates except one in genogroup Id. One isolate collected in 2007 was placed within the SVCV Ia genogroup. More importantly, the study al...

ÐIn most data-mining applications where induction is used as the primary tool for knowledge extraction from real-world databases, it is difficult to precisely identify a complete set of relevant attributes. This paper introduces a new rule induction algorithm called Rule Induction Two In One (RITIO), which eliminates attributes in the order of decreasing irrelevancy. Like ID3-like decision tree...

This paper describes eecient methods for exact and approximate implementation of the MIN-FEATURES bias, which prefers consistent hypotheses deenable over as few features as possible. This bias is useful for learning domains where many irrelevant features are present in the training data. We rst introduce FOCUS-2, a new algorithm that exactly implements the MIN-FEATURES bias. This algorithm is e...

Our work is in machine learning, a subfield of artificial intelligence. We describe a variant of the ID3 algorithm [5] which is attuned to the situation that every feature’s value-set is linearly ordered and finite. We then seek economical training sets, that is, ones which are small in size but result in learned decision trees of high accuracy. Our search focuses on geometric properties of the...

The problem of deciding which subset of values of a categorical-valued attribute to branch on during decision tree generation is addressed. Algorithms such as ID3 and C4 do not address the issue and simply branch on each value of the selected attribute. The GID3* algorithm is presented and evaluated. The GID3* algorithm is a generalized version of Quinlan’s ID3 and C4, and is a non-parametric v...

Many real-world domains bless us with a wealth of attributes to use for learning. This blessing is often a curse: most inductive methods generalize worse given too many attributes than if given a good subset of those attributes. We examine this problem for two learning tasks taken from a calendar scheduling domain. We show that ID3/C4.5 generalizes poorly on these tasks if allowed to use all av...

The rule extraction capability of neural networks is an issue of interest to many researchers. Even though neural networks o€er high accuracy in classi®cation and prediction, there are criticisms on the complicated and non-linear transformation performed in the hidden layers. It is dicult to explain the relationships between inputs and outputs and derive simple rules governing the relationship...

In this paper, we introduce a new approach to the classification of streaming data based on bootstrap aggregation (bagging). The proposed approach creates an ensemble model by using ID3 classifier, naïve Bayesian classifier, and k-Nearest-Neighbor classifier for a learning scheme where each classifier gives the weighted prediction. ID3, naïve Bayesian, and k-NearestNeighbor classifiers are very...