CompTIA Updated DY0-001 Exam Questions and Answers by minnie

→ Decision trees are supervised classification models that can be used to predict a categorical target variable (e.g., Habitat: Land or Sea) based on input features (e.g., Wrapper color, Wrapper shape, Animal type). They are interpretable, require minimal preprocessing, and are ideal for structured categorical data like this.

Why the other options are incorrect:

A: ARIMA (AutoRegressive Integrated Moving Average) is used for time-series forecasting, not classification.

B: Linear regression is used for predicting continuous numeric values, not categorical variables like "Land" or "Sea".

C: Association rules (like in market basket analysis) are used to discover relationships or co-occurrence among variables, not to build predictive models.

Official References:

CompTIA DataX (DY0-001) Study Guide – Section 4.1 & 4.2:“Decision trees are powerful classifiers for categorical output variables and allow for interpretable models based on feature splits.”

Machine Learning Textbook, Chapter 6:“Decision trees are ideal for early-stage model prototyping when the output is categorical and the data structure is tabular.”

→ An inner join returns only those records that have matching keys (employee IDs in this case) in both tables. Since each table provides a different attribute for the same entity (employee), an inner join is the most efficient and accurate method when focusing on employees present in both tables.

Why the other options are less ideal:

B & C: Left or right joins would include unmatched data, which may lead to nulls.

D: An outer join brings in all records from both tables and fills nulls where no matches exist, which may introduce irrelevant or incomplete entries.

Official References:

CompTIA DataX (DY0-001) Official Study Guide – Section 5.2:“Inner joins are most appropriate when combining datasets with matching keys to retain only relevant, intersecting records.”

SQL for Data Analysts, Chapter 3:“Use inner joins when combining tables on a common key to include only matched data for analysis.”

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