DP-100 Question #76: Real Exam Question with Answer & Explanation

Question

You are conducting feature engineering to prepuce data for further analysis. The data includes seasonal patterns on inventory requirements. You need to select the appropriate method to conduct feature engineering on the data. Which method should you use?

Options

• AExponential Smoothing (ETS) function.
• BOne Class Support Vector Machine module
• CTime Series Anomaly Detection module
• DFinite Impulse Response (FIR) Filter module.

Explanation

The question seeks an appropriate feature engineering method for data that includes seasonal patterns, such as inventory requirements.

Common mistakes.

• A. Exponential Smoothing (ETS) function is primarily a forecasting technique for time series, not a feature engineering method to extract or transform seasonal patterns for further analysis.
• B. One Class Support Vector Machine module is used for anomaly detection in unlabeled data, focusing on identifying outliers rather than engineering features from seasonal patterns.
• C. Time Series Anomaly Detection module is designed to identify unusual data points in time series, not to conduct general feature engineering on inherent seasonal patterns.

Concept tested. Feature engineering for seasonal time series

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