I have the following dataset. I would like to know which bacteria contribute more when comparing the location of the bacteria(categorical) and its pH(numeric).
For instance at the end I would like to say for example that a certain bacterial type is more frequently found in a certain location when looking at the temperature.
Bacillus Lactobacillus Janibacter Brevibacterium Lawsonella Location temperature Sample1 2 30 164 8 21 48 bedroom 27 Sample2 0 211 0 996 195 108 bedroom 35 Sample3 1 938 1 21 38 43 pool 45 Sample4 0 95 17 1 4 334 pool 10 Sample5 0 192 91 25 1207 1659 soil 14 Sample6 0 12 33 6 12 119 soil 21 Sample7 0 16 3 0 0 805 soil 12
The idea is to run randomforest to select those features (bacteria) that are more important when looking at both the location and the temperature.
Is a random forest suitable for this? When I run the following command I get the following error:
randomForest(Location+Temperature ~.,data=mydf) Error in Location + Temperature : non-numeric argument to binary operator.
From the error it looks that i cannot use a continuous and categorical variable together. How can I fix this?
Is for exemple convert the numeric temperature variable to ranges of temperatures as a categorical variables would be a solution ?
In fact I have tried and it worked by converting the numeric temperature to ranges and pasting the location so that i have a combination of location and temperature.
I get the list of important bacteria which is what I was looking for. Now how can I know which one contributes more to one location or another since my model i was using all sites? For example how to check that your important variables(let´s say Bacillus is the most important from the randomforest model ) is important in the pool location (how much variation it explains in the pool)?