lecture7 - Data Mining CS57300 Purdue University September...

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Unformatted text preview: Data Mining CS57300 Purdue University September 16, 2010 Predictive modeling: representation Data mining components Task specifcation: Prediction Data representation: Homogeneous IID data Knowledge representation Learning technique InFerence technique Descriptive vs. predictive modeling Descriptive models summarize the data Provide insights into the domain Focus on modeling joint distribution P(X) May be used for classication, but not primary goal Predictive models predict the value of one variable of interest given known values of other variables Focus on modeling conditional distribution P(Y | X) or decision boundary for Y Example: SPAM I was reading a little more about Tsalling entropy and trying to fgure out whether it would be appropriate For relational learning problems. One possibility is to use it For exponential random graph models, which have Features like the number oF triangles in the graph. Since these grow with graph size, it seems to be an "extensive" property that the Tsalling entropy is trying to model Don't Be Silly To Pay Hundred$ Or...
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This note was uploaded on 03/13/2012 for the course CS 573 taught by Professor Staff during the Fall '08 term at Purdue University-West Lafayette.

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lecture7 - Data Mining CS57300 Purdue University September...

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