Transcription of CHAPTER Logistic Regression - Stanford University
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CHAPTER Logistic Regression - Stanford University
Speech and Language Processing. Daniel Jurafsky & James H. Martin. Copyrightc 2019. Allrights reserved. Draft of October 2, Regression And how do you know that these fine begonias are not of equal importance? Hercule Poirot, in Agatha Christie sThe Mysterious Affair at StylesDetective stories are as littered with clues as texts are with words. Yet for thepoor reader it can be challenging to know how to weigh the author s clues in orderto make the crucial classification task: deciding this CHAPTER we introduce an algorithm that is admirably suited for discoveringthe link between features or cues and some particular outcome: Logistic , Logistic Regression is one of the most important analytic tools in the socialand natural sciences.
of the input features x i. The weight w i represents how important that input feature is to the classification decision, and can be positive (providing evidence that the in-stance being classified belongs in the positive class) or negative (providing evidence that the instance being classified belongs in the negative class). Thus we might
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