'Logit function' presentation slideshows

Logistic Regression I

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9. Binary Dependent Variables

9. Binary Dependent Variables. 9.1 Homogeneous models Logit, probit models Inference Tax preparers 9.2 Random effects models 9.3 Fixed effects models 9.4 Marginal models and GEE Appendix 9A - Likelihood calculations. 9.1 Homogeneous models.

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MaxEnt is useful here too

MaxEnt is useful here too. We last saw MaxEnt in the NLTK default tagger What is it doing?. Logistic regression. Very common machine learning technique Assign a positive/negative value to every feature Add up the values for features that are present The logit function tells

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