Question $5$

Please identity the following problems to be supervised, unsupervised, semisupervised, or reinforcement Learning problems.

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A communication company is trying to predict which current customer is going to transfer to another service provider by analyzing the corresponding data in the past $10$ years.

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Take a collection of $1,000,000$ different genes, and find a way to automatically group these genes into groups that are somehow similar or related by different variables, such as lifespan, location, roles, and so on$.$

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You have a lot of data about your blog$$s visitors. You are trying to detect different groups of similar visitors based on the data. The result may help you target your posts for each group.

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Given a patient with a tumor, we have to predict whether the tumor is malignant or benign.

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DeepMind$$s AlphaGo program beat the world champion at the game of Go$.$ It learned its winning policy by analyzing millions of games and then playing many games against itself.

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When you uploaded a few photos to Facebook, it automatically recognizes that the same person A shows up in photos $1,5,$ and $8,$ while another person B shows up in photos $2,5,$ and $6.$ The person you labeled before will be automatically labeled and you need to label person B so the system can name everyone in every photo.

A$.$

Semisupervised learning

B$.$

Unsupervised learning

C$.$

Reinforcement Learning

D$.$

Supervised learning