Learn which Amazon SageMaker Data Wrangler visualization is best for analyzing the distribution of car prices for a specific vehicle type in a dataset. Discover how histograms enable ML engineers to inspect value ranges.
Table of Contents
Question
A car company has dealership locations in multiple cities. The company uses a machine learning (ML) recommendation system to market cars to its customers.
An ML engineer trained the ML recommendation model on a dataset that includes multiple attributes about each car. The dataset includes attributes such as car brand, car type, fuel efficiency, and price.
The ML engineer uses Amazon SageMaker Data Wrangler to analyze and visualize data. The ML engineer needs to identify the distribution of car prices for a specific type of car.
Which type of visualization should the ML engineer use to meet these requirements?
A. Use the SageMaker Data Wrangler scatter plot visualization to inspect the relationship between the car price and type of car.
B. Use the SageMaker Data Wrangler quick model visualization to quickly evaluate the data and produce importance scores for the car price and type of car.
C. Use the SageMaker Data Wrangler anomaly detection visualization to Identify outliers for the specific features.
D. Use the SageMaker Data Wrangler histogram visualization to inspect the range of values for the specific feature.
Answer
D. Use the SageMaker Data Wrangler histogram visualization to inspect the range of values for the specific feature.
Explanation
A histogram is the most appropriate visualization for identifying the distribution of values for a specific feature, such as car prices for a particular type of vehicle.
Histograms group values into bins or intervals and show the frequency or count of data points falling into each bin. This allows you to see how the car prices are distributed – whether they are uniformly spread out, clustered around certain values, skewed to one end, bimodal with two peaks, etc.
By selecting the car type feature to subset the data and choosing car price as the feature to visualize, the histogram will display the range and frequency of price values just for that specific type of car. This gives insight into the price distribution.
The other options are not as suitable:
A. A scatter plot shows the relationship between two continuous variables, not the distribution of a single variable. It wouldn’t aggregate prices into bins.
B. A quick model produces importance scores indicating each feature’s relative influence on the target, but doesn’t show price distributions.
C. Anomaly detection identifies unusual outlier data points but doesn’t provide an overall view of the price value distribution.
Therefore, a histogram is the best choice for the ML engineer to identify how car prices are distributed for a specific car type using Amazon SageMaker Data Wrangler. The histogram’s binning will reveal insights about the range and frequency of price values.
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