knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
library(tidyverse) library(tidymine)
We often want to work out which variables are most relevant for predicting or describing another.
Correlation struggles with this because it is mainly limited to recognising linear patterns.
Here are some examples.
MINE statistics get around this problem.
mlb_2008 %>% tidymine(salary) %>% arrange(-mic)
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