MLS-C01 · Question #99
MLS-C01 Question #99: Real Exam Question with Answer & Explanation
The correct answer is A: Embed the numerical features using the t-distributed stochastic neighbor embedding (t-SNE). t-SNE can do segmentation or grouping as well. https://towardsdatascience.com/an-introduction-to-t-sne-with-python-example-5a3a293108d1
Question
A Machine Learning Specialist is given a structured dataset on the shopping habits of a company's customer base. The dataset contains thousands of columns of data and hundreds of numerical columns for each customer. The Specialist wants to identify whether there are natural groupings for these columns across all customers and visualize the results as quickly as possible. What approach should the Specialist take to accomplish these tasks?
Options
- AEmbed the numerical features using the t-distributed stochastic neighbor embedding (t-SNE)
- BRun k-means using the Euclidean distance measure for different values of k and create an elbow
- CEmbed the numerical features using the t-distributed stochastic neighbor embedding (t-SNE)
- DRun k-means using the Euclidean distance measure for different values of k and create box plots
Explanation
t-SNE can do segmentation or grouping as well. https://towardsdatascience.com/an-introduction-to-t-sne-with-python-example-5a3a293108d1
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