Free EMC D-DS-FN-23 Practice Exam with Questions & Answers

In logistic regression, the threshold determines the cutoff for classifying an outcome. If the probability exceeds the threshold (0.3 in this case), the model predicts the positive class—here, that the borrower will default.

The EXCEPT operator returns rows that exist in the result set of the first SELECT statement but not in the second. It removes duplicates and only shows the difference between the two datasets.

A Type I error occurs when the null hypothesis is rejected even though it is actually true. This is also known as a "false positive" in hypothesis testing.

The GROUPING extension in SQL OLAP is used to return a result for each output row, where 1 identifies a summary row and 0 identifies grouped rows. This helps distinguish between regular grouped rows and summary rows in the result set.

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.

Analysts value clarity and interpretability in data presentations. Clean, simple-to-understand visuals help them accurately assess the data, model outputs, and insights without unnecessary complexity.

The R-squared value is approximately 0.96, indicating that 96% of the variance in the data is explained by the model.

The Hadoop Distributed File System (HDFS) is a master/slave system designed to run on commodity hardware, meaning it can efficiently store large volumes of data across inexpensive, off-the-shelf hardware.

The formula for Naïve Bayes is:

For the renewal class, we are given:

● P(Class = Renewal) = 0.8 (since 80% renew the policy)

● P(Age > 65 years | Renewal) = 0.3

● P(Housing = Own | Renewal) = 0.9

● P(Renewal Month = August | Renewal) = 0.1

P(Renewal) = P(Renewal) × P(Age > 65 years | Renewal) × P(Housing = Own | Renewal) × P(Renewal Month = August | Renewal)

P(Renewal) = 0.8 × 0.3 × 0.9 × 0.1 = 0.0216

In a Moving Average (MA) process of order q, the current deviation from the mean is modeled as a linear combination of the previous q deviations (errors).