This paper reports first results of an empirical study of the precision of classification rules on an independent test set. We generated a large number of rules using a general co...
Random decision tree is an ensemble of decision trees. The feature at any node of a tree in the ensemble is chosen randomly from remaining features. A chosen discrete feature on a...
—In-field diagnosability of electronic components in larger systems such as automobiles becomes a necessity for both customers and system integrators. Traditionally, functional ...
This paper presents a low-overhead scheme for built-in self-test of circuits with scan. Complete (100%) fault coverage is obtained without modifying the function logic and without...
We present an algorithm, called the offset tree, for learning in situations where a loss associated with different decisions is not known, but was randomly probed. The algorithm i...