Last answered:

17 Dec 2022

Posted on:

08 Dec 2022


Minimise or maximise the objective function

In video Machine Learning(ML) Techniques it says objective function is a measure how far it is from the target. One would thought minimise the objective function should be good as it will reduce the distance from the target. However, in video Machine Learning(ML) Types of Machine Learning, when talked about reinforcement learning, it says to maximise the objective function. So should we minimise or maximise the objective function?

1 answers ( 0 marked as helpful)
Posted on:

17 Dec 2022


Hi Josh!

Thanks for reaching out.

In fact, you've guessed it. Depending on the type of machine learning applied, the objective function should be minimised or optimized.
When we are doing supervised or unsupervised learning, we are trying to be closer to the target; in other words, we'd like to minimize the distance away from the target. That's when we'd like to minimize the objective function.
When we are referring to reinforcement learning, we'd like to reinforce our algorithm, so we'd like to maximize the related reward. Then, we are maximizing the objective function.

Hope this helps.
Kind regards,

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