Multinomial Logistic Regression and Maximum Entropy DATA-SCIENCE-OPTIMIZE Practice Questions (Page 4)

Questions 16–16

1. 16application · medium

   A data scientist is building a model to classify customer support tickets into one of four categories: Billing, Technical, Account, or Other. The team has 10,000 labeled tickets and wants the model to output a probability distribution over the four classes for each ticket. The data scientist decides to use multinomial logistic regression. Which component of the model directly ensures that the output for each ticket is a valid probability distribution (all values between 0 and 1, summing to 1)?

   • AThe maximum likelihood estimation procedure used to fit the model coefficients
   • BThe softmax function applied to the linear combination of features for each class
   • CThe use of binary indicator features for each ticket category
   • DThe gradient descent optimizer that updates the weights during training
   Reveal Solution Discussion Select an answer first