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26 lines
600 B
Plaintext
26 lines
600 B
Plaintext
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2
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know linear regression very well
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3
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make sure you know R^2 and RSE and so on statistics
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MSE, is this related to something called D^2? might have misheard the prof with that one.
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4
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given some data set: what method to use?
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quantitative or qualitative? --> then what method specifically? need to explain why to choose this method. bias-variance tradeoff; will the bias be high or low, and why?
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5
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bootstraps, cross-examination
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6
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uneven classes (look at for example LDA on Credit Data)
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7
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PCR and PCA is very useful but probably less important for the exam
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