class_10_05

class_10_05 - Statistical Data Mining ORIE 474 Fall 2007...

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Statistical Data Mining ORIE 474 Fall 2007 Tatiyana Apanasovich 10/05/07 Regression (III)
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Collect data Preliminary checks on data quality Diagnostics for relationships and strong interactions Determine several potentially useful subsets of explanatory variables; including known essential variables Investigate curvature and interaction effects more fully Study residuals and other diagnostics Select tentative model Are remedial measures needed? Are remedial measures needed? Validity checks? Final Regression model NO NO YES YES YES NO Remedial measures Remedial measures Data collection and preparation Reduction of number of explanatory variables Model refinement and selection Model validation
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Selection Problem: Predict Y from X 1 ,…,X p Do we need all variables X 1 ,…,X p for accurate prediction? Some X variables may be uncorrelated to Y Some X variables may be redundant Interaction of individual variable X with Y: Linear dependence (Y numerical)
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This note was uploaded on 12/23/2009 for the course ORIE 474 at Cornell.

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class_10_05 - Statistical Data Mining ORIE 474 Fall 2007...

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