The rcode to load and clean the dataset and to run the analysis is available on my github: gist.github.com/musa5237/2e41fa4ec8fe36b34d374e0879523754 Some additional updates to the video: 03:06 -- To load a csv into your environment, the code should be read.csv(file.choose(), sep= ‘,’, header=T) 03:31 -- Type.1 is the pokemon type (e.g., water, fire, etc.) not the name. I left the name out of the dataset with select(). 29:43 -- I should clarify that the mean decrease in accuracy and mean decrease in gini agreed only on which feature is most important. 41:57 -- The hash notes should read default arguments for regression not classification.
The rcode to load and clean the dataset and to run the analysis is available on my github: gist.github.com/musa5237/2e41fa4ec8fe36b34d374e0879523754
Some additional updates to the video:
03:06 -- To load a csv into your environment, the code should be read.csv(file.choose(), sep= ‘,’, header=T)
03:31 -- Type.1 is the pokemon type (e.g., water, fire, etc.) not the name. I left the name out of the dataset with select().
29:43 -- I should clarify that the mean decrease in accuracy and mean decrease in gini agreed only on which feature is most important.
41:57 -- The hash notes should read default arguments for regression not classification.