Building a model using machine learning that can classify the sentiment of natural language text often requires an extensive set of labeled training data from the same domain as t...
This work presents decision trees adequate for the classification of series data. There are several methods for this task, but most of them focus on accuracy. One of the requirem...
We present Confidence-based Feature Acquisition (CFA), a novel supervised learning method for acquiring missing feature values when there is missing data at both training and test...
Marie desJardins, James MacGlashan, Kiri L. Wagsta...
The bias-variance decomposition is a very useful and widely-used tool for understanding machine-learning algorithms. It was originally developed for squared loss. In recent years,...
In this paper we describe a new approach to extract element labels from Web form interfaces. Having these labels is a requirement for several techniques that attempt to retrieve a...