The objective function is the function that you want to minimise or maximise in your problem. The expression "objective function" is used in several different contexts (e.g. machine learning or linear …

A loss function is a part of a cost function which is a type of an objective function. All that being said, thse terms are far from strict, and depending on context, research group, background, can shift and …

Aug 6, 2021 · The objective function is the most general term that can be used to refer to a cost (or loss) function, to a utility function, or to a fitness function, so, depending on the problem, you either want to …

Dec 15, 2021 · Explore related questions objective-functions generative-adversarial-networks logarithm See similar questions with these tags.

Jul 29, 2019 · I find the terms cost, loss, error, fitness, utility, objective, criterion functions to be interchangeable, but any kind of minor difference explained is appreciated.

What do the variables mean in the SVM objective function? Ask Question Asked 11 years, 5 months ago Modified 10 years, 2 months ago

Jan 27, 2015 · Why not choose some other objective function to minimize? I understand that, for technical reasons, the quadratic function is nicer than some other functions, e.g., sum of absolute …

Feb 3, 2015 · PCA objective function: what is the connection between maximizing variance and minimizing error? Ask Question Asked 13 years, 5 months ago Modified 10 years, 10 months ago

Jan 30, 2021 · In my experience, the fitness function is a way to define the goal of a genetic algorithm. It provides a way to compare how "good" two solutions are, for example, for mate selection and for …

For this the objective function I am using is objective = 'binary:logistic'. I did built an Xgboost model using the above ojective function and my evaluation metric being the average precision score. The score …