The “multinom” Function in R

• Package: nnet

• Purpose: Fits multinomial logistic regression models.

• General class: Machine learning

• Required argument(s):

• formula: A formula specifying the model.

• data: The dataset to be used.

• Notable optional arguments:

• weights: Optional case weights.

• trace: Logical indicating whether to print progress trace.

• maxit: Maximum number of iterations.

• Example:

• # Load the nnet library
  library(nnet)
  
  # Fit a multinomial logistic regression model using the iris dataset
  model <- multinom(Species ~ ., data = iris, maxit = 100)
  
  # Print the model summary
  summary(model)

• This example demonstrates how to use the multinom function from the nnet package to fit a multinomial logistic regression model on the iris dataset. The formula Species ~ . specifies that Species is the response variable and all other columns are predictors. Optional arguments like trace and maxit control the printing of progress trace and the maximum number of iterations, respectively. The summary function is then used to print the model summary.