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Unverified Commit a4d7b0b7 authored by Dasani Madipalli's avatar Dasani Madipalli Committed by GitHub
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Update README.md

adding the multinomial vs ordinal infographic
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...@@ -31,7 +31,8 @@ Logistic Regression does not offer the same features as Linear Regression. The f ...@@ -31,7 +31,8 @@ Logistic Regression does not offer the same features as Linear Regression. The f
There are other types of Logistic Regression, including Multinomial and Ordinal. Multinomial involves having more than one categories - "Orange, White, and Striped". Ordinal involves ordered categories, useful if we wanted to order our outcomes logically, like our pumpkins that are ordered by a finite number of sizes (mini,sm,med,lg,xl,xxl). There are other types of Logistic Regression, including Multinomial and Ordinal. Multinomial involves having more than one categories - "Orange, White, and Striped". Ordinal involves ordered categories, useful if we wanted to order our outcomes logically, like our pumpkins that are ordered by a finite number of sizes (mini,sm,med,lg,xl,xxl).
> Infographic on the difference between multinomial vs. ordinal logistic regression in the context of our pumpkin dataset: there are images here for multinomial https://www.codespeedy.com/multinomial-logistic-regression-in-python/ and for ordinal check this out: http://fa.bianp.net/blog/static/images/2013/ordinal_1.png - you can show the pumpkin sizes in a line - the smaller, the more expensive by the bushel, for example. ![Multinomial vs Ordinal](https://github.com/jlooper/ml-for-beginners/blob/main/2-Regression/4-Logistic/images/Multinomial_Vs_Ordinal.png)
> Infographic by [Dasani Madipalli](https://twitter.com/dasani_decoded)
### It's Still Linear ### It's Still Linear
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