Multinomial logistic regression: Difference between revisions

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As a log-linear model: Grammatical correction
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As a result, it is conventional to set <math>C = -\boldsymbol\beta_K</math> (or alternatively, one of the other coefficient vectors). Essentially, we set the constant so that one of the vectors becomes 0, and all of the other vectors get transformed into the difference between those vectors and the vector we chose. This is equivalent to "pivoting" around one of the ''K'' choices, and examining how much better or worse all of the other ''K''-1 choices are, relative to the choice we are pivoting around. Mathematically, we transform the coefficients as follows:
 
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