Measuring the Similarity between Implicit WWW2009 EPrints Www2009 Eprints Form

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hello again so today's lecture we're going to talk about measuring data similarity measuring similarity between different data sets different data points um this is just an introduction to some concepts that we'll reuse over and over and we may introduce other similarity measures later on but the idea is just to now that we've talked about definition of what data is and what different types of data there are a lot of data analysis machine learning clustering pattern recognition is going to be saying are these two points that we have two data points whether it's representing people in their biographical information or two images or two states of your um car or two different sensor readings whether those two data points are similar or different it's a really fundamental thing that we use really so much that's almost almost everything comes down to being based on similarity and dissimilarity and probability metrics between sets of points sort of define these in various different ways for