D-DS-FN-23 Exam Dumps : Dell Data Science Foundations

An itemset is a set of discrete variables (or items) that are linked or appear together in a transaction or dataset, commonly used in association rule mining to find relationships between items.

Recalibration of the model should be assessed during the Operationalize phase, as this is when the model is deployed and monitored in real-world conditions, making it easier to identify if it requires adjustments based on its performance.

The naïve Bayes conditional independence assumption is applied to simplify the probability calculations by assuming that the features are independent given the class label. This reduces the complexity of the model and makes computation feasible even with many features.