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Reinforcement Learning In Action - Multi Label Classification

 
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Hi Alexander and Brandon.

Can Reinforcement Learning be used for Multi-Label classification?
We have a potential application where the labels run to tens or perhaps a few hundred thousand different labels. Is Reinforcement Learning something we should be investigating for this?

Thanks
Don.
 
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Don Horrell wrote:Hi Alexander and Brandon.

Can Reinforcement Learning be used for Multi-Label classification?
We have a potential application where the labels run to tens or perhaps a few hundred thousand different labels. Is Reinforcement Learning something we should be investigating for this?

Thanks
Don.



If it's a static sort of classification problem like image classification, then RL wouldn't be the right way to conceptualize the problem. However, if your classification problem exists in a dynamic environment, such as deciding which advertisement to display for a particular user, which may change depending on dynamic user and sitewide data, then RL could be useful (see multi-armed bandits). RL is a framework for decision-making in a dynamic environment.
 
Don Horrell
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Thank you for your interesting comment.

Could you explain a bit more about what you mean by a "dynamic environment" please?

So, if Reinforcement Learning can select an advertisement for a user, that sounds similar to classification (of images?). A person walks past a smart advertising board which somehow identifies that person and the "label" is the type of advert that will be displayed for that person.
Or have I got the wrong end of the stick? Or perhaps even the wrong stick?


Cheers
Don.
 
Brandon Brown
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Don Horrell wrote:Thank you for your interesting comment.

Could you explain a bit more about what you mean by a "dynamic environment" please?

So, if Reinforcement Learning can select an advertisement for a user, that sounds similar to classification (of images?). A person walks past a smart advertising board which somehow identifies that person and the "label" is the type of advert that will be displayed for that person.
Or have I got the wrong end of the stick? Or perhaps even the wrong stick?


Cheers
Don.



Yes the label would be one of some finite number of possible advertisements. The objective here, however, would be for the RL algorithm to optimize the clickthrough rate. So rather than an image classification where the algorithm is trained based on whether or not the classification is correct or not, the decision here is not binary. There is no one correct ad, some ads will result in more clicks (if these are ads on a website) than others, and the goal is to learn which ad will cause a potential customer to be most likely to respond to the ad by buying.

A dynamic environment just to mean that again, the decision isn't a correct/incorrect labeling, but a set of actions that lead to more or less of some outcome (points in a game, clicks for ads, money if trading stocks, etc)
 
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