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[D] Quick question about differentiating supervised and unsupervised learning problems (alien.top)

submitted 10 months ago by RepresentativeBowl35@alien.top to c/machinelearning@academy.garden

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I was doing an online quiz on ML where I came across this question with these series of answer combination, and it kind of confused me about the concepts to differentiate between unsupervised and supervised learning problems. Based on my knowledge, anomaly detection and customer segmentation are typically carried out on unlabelled data, which makes them to be classified as an unsupervised learning problem. However, after doing some research online, I saw that anomaly detection could possibly be done using supervised learning. So my question here is, can anomaly detection and customer segmentation be classified as a supervised learning problem?

I have listed the quiz question here for your reference:

Which of the following is an example of a supervised learning problem?

A. Clustering similar documents based on their content

B. Detecting anomalies in network traffic data

C. Predicting the price of a house based on its features

D. Segmenting customers into different groups based on their purchasing behavior

a. A and B only

b. B and C only

c. C and D only

d. A, C, and D only

e. All of the above are examples of supervised learning problems.

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[–] lambdasintheoutfield@alien.top 1 points 10 months ago

I gave all the information needed to answer that question. This sub isn’t really about academic assistance, and me telling you the answer outright serves little value.

Do keep in mind that actual ML, whether you go into academic research or into the engineering side ,will require you to answer questions with far more nuance than what this quiz question asks, which is simply about basic definitions.