I am working with the R programming language. I created a decision tree for this dataset in R (to predict whether the "diabetes" column is either "pos" or "neg"):
#load libraries
library(pdp)
library(C50)
#load data
data(pima)
#remove na's
new_data = na.omit(pima)
#format data
new_data$age = as.factor(ifelse(new_data$age >30, "1", "0"))
new_data$pregnant = as.factor(ifelse(new_data$pregnant >2, "1", "0"))
#run model
tree_mod <- C5.0(x = new_data[, 1:8], rules = TRUE, y = new_data$diabetes)
Here is my question: I am trying to obtain a column of "predictions" made by the model for new observations. I am then want to take this column and append it to the original dataset.
Using the following link, https://cran.r-project.org/web/packages/C50/vignettes/C5.0.html, I used the "predict" function:
#pretend this is new data
new = new_data[1:10,]
#run predictions
pred = predict(tree_mod, newdata = new[, 1:8])
But this produces the following error:
Error in x[j] : invalid subscript type 'closure'
Can anyone please show me how to do this?
I am trying to create something like this ("prediction_made_by_model"):
pregnant glucose pressure triceps insulin mass pedigree age diabetes prediction_made_by_model
4 0 89 66 23 94 28.1 0.167 0 neg pos
5 0 137 40 35 168 43.1 2.288 1 pos neg
7 1 78 50 32 88 31.0 0.248 0 pos neg
9 0 197 70 45 543 30.5 0.158 1 pos pos
14 0 189 60 23 846 30.1 0.398 1 pos neg
15 1 166 72 19 175 25.8 0.587 1 pos pos
Thanks!
I was able to figure it out. For some reason, this was not working before:
pred = predict(tree_mod, newdata = new[, 1:8])
new$prediction_made_by_model = pred