Discriminant Analysis, k-Nearest Neighbors, and Naïve Bayes are analytic methods used to ______ events.

• A. Visualize events
• B. Summarize events
• C. Predict and categorize events
• D. Forecast probabilities

Answer: (C)

These methods are used for classifying new observations into predefined categories based on their features. Discriminant analysis builds a model of how each class distributes the data and uses it to assign a new observation to a class, often along with a probability of membership. k-Nearest Neighbors classifies by looking at the closest labeled examples and taking a majority vote to assign a label. Naive Bayes applies Bayes’ theorem with a simplifying independence assumption to compute the posterior probability for each class and choose the most probable one. While they can produce probability estimates, the core goal across these techniques is to predict or assign a category to events.