An analyst has a sufficient volume of data to perform a 3-way partition of the data into training, validation, and test sets to perform honest assessment during the model building process.What is the purpose of the training data set?
Refer to the confusion matrix:Calculate the sensitivity. (0 - negative outcome, 1 - positive outcome)Click the calculator button to display a calculator if needed.
The total modeling data has been split into training, validation, and test data. What is the best data to use for model assessment?
What is a drawback to performing data cleansing (imputation, transformations, etc.) on raw data prior to partitioning the data for honest assessment as opposed to performing the data cleansing after partitioning the data?
A company has branch offices in eight regions. Customers within each region are classified as either "High Value" or "Medium Value" and are coded using the variable name VALUE. In the last year, the total amount of purchases per customer is used as the response variable.Suppose there is a significant interaction between REGION and VALUE. What can you conclude?
SIMULATION -A linear model has the following characteristics:*A dependent variable (y)*One continuous variable (xl), including a quadratic term (x12)*One categorical (d with 3 levels) predictor variable and an interaction term (d by x1)How many parameters, including the intercept, are associated with this model?Enter your numeric answer in the space below. Do not add leading or trailing spaces to your answer.
