Explanation:
The question asks for two visualizations to identify outliers in data. Box plots (B) are specifically designed to show data distribution, quartiles, and outliers as points beyond the whiskers. Scatter plots (E) can reveal outliers as points that deviate significantly from the main cluster pattern. The community discussion shows 100% consensus on BE, with multiple comments confirming that box plots and scatter plots are effective for outlier detection. Other options are less suitable: Venn diagrams (A) show set relationships, ROC curves (C) evaluate classification performance, and random forest diagrams (D) are not standard visualization tools for outlier detection.
You are creating a machine learning model and need to identify outliers in the data.
Which two visualizations can you use? Each correct answer presents a complete solution.
A
Venn diagram
B
Box plot
C
ROC curve
D
Random forest diagram
E
Scatter plot
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