Differentiating anomalous network activity from normal network traffic is difficult and tedious. A human analyst must search through vast amounts of data to find anomalous sequenc...
Most recent research of scalable inductive learning on very large dataset, decision tree construction in particular, focuses on eliminating memory constraints and reducing the num...
Classification, which involves finding rules that partition a given da.ta set into disjoint groups, is one class of data mining problems. Approaches proposed so far for mining cla...
Abstract. In the biometric field, different experts are combined to improve the system reliability, as in many application the performance attained by individual experts (i.e., d...
We present a novel classification-based algorithm called GeneClass for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple orga...
Manuel Middendorf, Anshul Kundaje, Chris Wiggins, ...