Assume that you are the data scientist for ACME sporting goods and you have been asked to develop a predictive model that will help the company determine which products to produce and in what quantities for the upcoming sports season. You have historical data from many years with data that includes all of the factors that impacted sales of different types of products. Which of the following techniques are you most likely to use?

Select one:

a. Linear Regression

b. K-nearest neighbors classification

c. Bayes Classifier

d. Hierarchical clustering