We address the issue of compiling ML pattern matching to compact and efficient decisions trees. Traditionally, compilation to decision trees is optimized by (1) implementing decis...
Abstract. The aim of this work is to forecast future events in financial data sets, in particular, we focus our attention on situations where positive instances are rare, which fal...
This paper introduces a new technique for predicting latent software bugs, called change classification. Change classification uses a machine learning classifier to determine wheth...
Sunghun Kim, E. James Whitehead Jr., Yi Zhang 0001
We consider the existence of a linear weak learner for boosting algorithms. A weak learner for binary classification problems is required to achieve a weighted empirical error on t...
In this paper, we present new probabilistic models for identifying bird species from audio recordings. We introduce the independent syllable model and consider two ways of aggregat...