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In a classification problem, I cannot use a simple logit model if my data label (aka., dependent variable) has more than two categories. That leaves me with multinomial regression and Linear Discriminant Analysis (LDA) and the likes. Why is it that multinomial logit is not as popular as LDA in machine learning? What is the particular advantage that LDA offers?

Navid Asgari
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  • Linear Discriminant Analysis and Multinomial Logistic Regression are used for two very different things. It is not fair to compare them. – Mohsin Jul 18 '19 at 12:06
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    It looks like https://stats.stackexchange.com/ is geared toward questions specifically about ML & the like. (Based on their description, "Q&A for people interested in statistics, machine learning, data analysis, data mining, and data visualization.") Might be a better fit there. – jwismar Jul 18 '19 at 12:06

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