Finding Highly Correlated Pairs Efficiently with Powerful Pruning ∗ Joan Feigenbaum

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Date: 2006-08-31 13:51:39 Information science Information retrieval Search algorithms Hashing Information MinHash Hash table Hash function Association rule learning Pearson product-moment correlation coefficient Apriori algorithm Bloom filter		Finding Highly Correlated Pairs Efficiently with Powerful Pruning ∗ Joan Feigenbaum Add to Reading List Source URL: cs-www.cs.yale.edu Download Document from Source Website File Size: 184,04 KB Share Document on Facebook

	Finding Highly Correlated Pairs Efficiently with Powerful Pruning ∗ Joan Feigenbaum DocID: 1qQRL - View Document
	The Linear Regression (r2) Test Correlation – “Correlation does not imply causation” Whenever you make a scatterplot graph, you can produce a statistic called the Pearson Productmoment Correlation Coefficient (r). DocID: 1qM6k - View Document
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	Repeated Measures Analysis with Discrete Data Using the SAS System Gordon Johnston, SAS Institute Inc., Cary, NC members may be correlated because of hereditary factors. DocID: 1q9j9 - View Document
	Basic Quantitative Analysis Week 1 Quiz: Correlation Note: The weekly quiz is essential for passing the final exam. The solutions are released each week. In this quiz, we review concepts related to correlation and covari DocID: 1pPKt - View Document