- This research presents a classifier that aims to provide insight into a dataset in addition to achieving classification accuracies comparable to other algorithms. The classifier called, Automated Weighted Sum (AWSum) uses a weighted sum approach where feature values are assigned weights that are summed and compared to a threshold in order to classify an example. Though naive, this approach is scalable, achieves accurate classifications on standard datasets and also provides a degree of insight. By insight we mean that the technique provides an appreciation of the influence a feature value has on class values, relative to each other. AWSum provides a focus on the feature value space that allows the technique to identify feature values and combinations of feature values that are sensitive and important for a classification.
This is particularly useful in fields such as medicine where this sort of micro-focus and understanding is critical in classification.
(from crpit.com)
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