Abstract. This paper presents k-NN as an approximator for time series prediction problems. The main advantage of this approximator is its simplicity. Despite the simplicity, k-NN c...
Classification is one of the most essential tasks in data mining. Unlike other methods, associative classification tries to find all the frequent patterns existing in the input...
During built-in self-test (BIST), the set of patterns generated by a pseudo-random pattern generator may not provide a sufficiently high fault coverage. This paper presents a new ...
Input selection is an important consideration in all large-scale modelling problems. We propose that using an established noise variance estimator known as the Delta test as the ta...
Background: The joint analysis of several categorical variables is a common task in many areas of biology, and is becoming central to systems biology investigations whose goal is ...
Corinne Dahinden, Giovanni Parmigiani, Mark C. Eme...