Generating Polynomial Features in R

Question

Is there an optimized way to perform this function "PolynomialFeatures" in R? I'm interested in creating a matrix of polynomial features i.e. interactions between two columns among all columns but I can't find a base function or a package that does this optimally in R and I don't want to import data from a Python script using sklearn's PolynomialFeatures function into R.

The idea is to transform this:

array([[0, 1],
       [2, 3],
       [4, 5]])

into this:

array([[ 1.,  0.,  1.,  0.,  0.,  1.],
       [ 1.,  2.,  3.,  4.,  6.,  9.],
       [ 1.,  4.,  5., 16., 20., 25.]])

Intercept and only-interaction options are well, optional. I could expand-omit those myself.

Answer 1

You can use two methods: one that takes a formula argument or if you are not using formula you can use model.matrix.

You can do the following:

# Using the same data from the question:
data <- data.table(A = c(0, 2, 4), 
                   B = c(1, 3, 5))

> data

   A B
1: 0 1
2: 2 3
3: 4 5

If only the raw data and the interactions are required

formula = y ~ .^2 

model.matrix(formula, data=data)
  (Intercept) A B A:B
1           1 0 1   0
2           1 2 3   6
3           1 4 5  20

If raw data, squared columns, interactions and intercept are needed, just like the question

You can use the following formula for all variables:

formula = y ~ .^2 + poly(var, 2, raw=TRUE)[, 2] ... etc

In addition you can paste the variables names automatically. Formula based on this post

formula <- as.formula(paste(' ~ .^2 + ',paste('poly(',colnames(data),',2, raw=TRUE)[, 2]',collapse = ' + ')))

> formula 

~.^2 + poly(A, 2, raw = TRUE)[, 2] + poly(B, 2, raw = TRUE)[, 2]

> model.matrix(formula, data=data)

  (Intercept) A B poly(A, 2, raw = TRUE)[, 2] poly(B, 2, raw = TRUE)[, 2] A:B
1           1 0 1                           0                           1   0
2           1 2 3                           4                           9   6
3           1 4 5                          16                          25  20

The resulting dataframe is identical to the array in the question.

If squared columns, interactions and intercept are needed.

> formula <- as.formula(paste(' ~ A:B + ',paste('poly(',colnames(data),',2, raw=TRUE)[, 2]',collapse = ' + ')))

> formula
~A:B + poly(A, 2, raw = TRUE)[, 2] + poly(B, 2, raw = TRUE)[, 2]

>  model.matrix(formula, data=data)
  (Intercept) poly(A, 2, raw = TRUE)[, 2] poly(B, 2, raw = TRUE)[, 2] A:B
1           1                           0                           1   0
2           1                           4                           9   6
3           1                          16                          25  20