A community radio station wants to discover groups of listening sessions that sound similar. Staff have not defined personas such as morning-news or late-jazz, and they will name the groups after the model runs. Which technique should they use?
Select an answer to reveal the explanation.
Short Explanation
Think of making piles of similar listening sessions first and naming them after you see what landed. That is clustering: no pre-set personas. Classification would need the names first, and a file on disk does not make this a computer-vision job.
Full Explanation
Clustering finds groups in unlabeled examples and leaves naming until after the run, which matches the station's request. Classification needs pre-set persona labels that staff said they do not have. Regression predicts a continuous number, not a discovered group. Storing sessions as files does not make the job computer vision.