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 …

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, …

What is the "binary:logistic" objective function in XGBoost? Ask Question Asked 7 years, 7 months ago Modified 5 years, 8 months ago

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.

Oct 19, 2020 · 23 I am looking at few competitions in kaggle where people used tweedie loss or poisson loss as objective function for forecasting sales or predicting insurance claims. Can …

What do the variables mean in the SVM objective function? Ask Question Asked 11 years, 4 months ago Modified 10 years, 1 month ago

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 …

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, …

Aug 25, 2020 · The help page of XGBoost specifies, for the objective parameter (loss function): reg:gamma: gamma regression with log-link. Output is a mean of gamma distribution. It might …

Feb 7, 2015 · 68 Principal component analysis can use matrix decomposition, but that is just a tool to get there. How would you find the principal components without the use of matrix …