This is more like a general, brainstroming query rather than a question.
So here it goes.
Suppose, I have 1000 items which I can sell on a website at any given day.
On any given day, I can sell (lets say) only 100 items..
And lets say, the obvious goal is to sell the maximum number of products any given day (maximimzing revenue)..
What is the best way to solve this problem. The problem being.. how do i select which 100 products of 1000 to select??I am sure, with this information it is pretty hard.. If I have to solve it using machine learning, which category will this problem fall into.
This is not supervised learning.. ?
Basically, I am just looking for the people around here to throw me some ideas.. 🙂
Thanks
This is more like a general, brainstroming query rather than a question. So here
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This is a variation of the multi-armed bandit problem. The most basic way of optimizing your profit is to pick a number ε є [0,1], then for each of the products you select choose the most popular one with probability (1-ε) or random with probability ε. This way, over time, you will have increasingly accurate popularity estimates for each product, while keeping your total profits high. More sophisticated approaches include tracking upper confidence bounds on product popularity.