Regression is essentially a statistical approach used to find the relationship between variables. In machine learning, this is used to predict the outcome of an event based on the relationship between variables obtained from the dataset.
As we've seen with prior options for training a model, the product documentation gives us a very good example exercise we can use to illustrate the regression approach to machine learning: training a model to predict the amount of money a customer is likely to spend on a trip to an outdoor equipment store.
Again, we'll go over the appropriate steps required for this exercise. For this exercise, we will choose the following:
- PURCHASE_AMOUNT (which is the average amount of money the customer has spent on each visit to the store) as our label column
- GENDER, AGE, MARITAL_STATUS, and PROFESSION as our feature columns
Next, as...
