One error you may encounter in R is:

Error in terms.formula(formula, data = data) : 
  invalid model formula in ExtractVars

This error occurs when you attempt to fit a in R and incorrectly specify one or more of the variables in the formula.

This tutorial shares exactly how to fix this error in practice.

How to Reproduce the Error

Suppose we create the following data frame in R:

#create data frame
df <- data.frame(rating=c(88, 94, 99, 90, 76, 78, 81, 88),
                 points=c(14, 17, 22, 24, 25, 22, 29, 31),
                 assists=c(7, 7, 6, 12, 10, 11, 17, 2),
                 rebounds=c(7, 8, 8, 12, 9, 5, 11, 15))

#view data frame
df

  rating points assists rebounds
1     88     14       7        7
2     94     17       7        8
3     99     22       6        8
4     90     24      12       12
5     76     25      10        9
6     78     22      11        5
7     81     29      17       11
8     88     31       2       15

Now suppose we attempt to use the rpart() function to fit a decision tree model to the data:

library(rpart)

#attempt to fit decision tree model to data
model <- rpart(rating ~ "points" + "assists" + "rebounds", data = df)

Error in terms.formula(formula, data = data) : 
  invalid model formula in ExtractVars

We receive an error because we used quotations around the predictor variable names, which is not allowed in the formula.

How to Fix the Error

The way to fix this error is to simply remove the quotations around the variable names and write the formula as follows:

library(rpart)

#fit decision tree model
model <- rpart(rating ~ points + assists + rebounds, data = df)

#view summary of model
summary(model)Call:
rpart(formula = rating ~ points + assists + rebounds, data = df)
  n= 8 

    CP nsplit rel error xerror xstd
1 0.01      0         1      0    0

Node number 1: 8 observations
  mean=86.75, MSE=55.1875

We’re able to successfully fit the model without any errors because we removed the quotations from the predictor variables in the formula.

The following tutorials explain how to fix other common errors in R: