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

MAD in MADlib stands for Multiple Access Design, which is a library for scalable in-database analytics, including machine learning and statistical methods.

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.

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.