I have a N-way frequency table generated from a regression model fit. This is a reproducible example of such table:
data("CO2") lm.fit = lm(uptake ~ Type + Treatment, data = CO2) lm.fit$coefficients test = count(CO2, c('Type','Treatment')) test$res = predict(lm.fit, newdata = test) test$freq = NULL
I am trying to visualize
test as a decision tree with nodes as
res as leaves. I would interpret it as the path the regression model takes, leading to the final value for a particular segment.
I am not able to generate a tree with
test. I am also open to other novel ways of visualizing these results. My original problem has many categorical variables, so I am looking for a customizable visualization, something from