Luke M. Davis

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The problem of time series classification (TSC), where we consider any real-valued ordered data a time series, presents a specific machine learning challenge as the ordering of variables is often crucial in finding the best discriminating features. One of the most promising recent approaches is to find shapelets within a data set. A shapelet is a time(More)
Until recently, the vast majority of data mining time series classification (TSC) research has focused on alternative distance measures for 1-Nearest Neighbour (1-NN) classifiers based on either the raw data, or on compressions or smoothing of the raw data. Despite the extensive evidence in favour of 1-NN classifiers with Euclidean or Dynamic Time Warping(More)
This research is part of a wider project to build predictive models of bone age using hand radiograph images. We examine ways of finding the outline of a hand from an X-ray as the first stage in segmenting the image into constituent bones. We assess a variety of algorithms including contouring, which has not previously been used in this context. We(More)
A facile ambient temperature route to the fabrication of surface silver-metallized polyimide films is described. Silver(I) trifluoromethanesulfonate or silver(I) nitrate and a polyimide, derived from 2,2-bis(3,4-dicarboxyphenyl)hexafluoropropane dianhydride and an equimolar amount of 4,4'-oxydianiline and 3,5-diaminobenzoic acid, were dissolved together in(More)
Reflective and surface conductive polyimide films were prepared by the incorporation of silver(I) acetate and trifluoroacetylacetone into a dimethylacetamide solution of the poly(amic acid) formed 3,3',4,4'-oxidiphthalic dianhydride (ODPA) and 4,4'-oxidianiline (4,4'-ODA). Thermal curing of (trifluoroacetylacetonato)silver(I)-poly(amic acid) films led to(More)
Many different rule interestingness measures have been proposed in the literature; we show that, under two assumptions, at least twelve of these measures are proportional to Confidence. We consider rules with a fixed consequent, generated from a fixed data set. From these assumptions, we prove that Satisfaction, Ohsaki’s Conviction, Added Value, Brin’s(More)