CODEWITHSUNDEEP
revaluationgbm
acre
acre

Reputation: 1

R: Evaluate Gradient Boosting Machines (GBM) for Regression

Which are the best metrics to evaluate the fit of a GBM algorithm in R (metrics, graphs, ratios)? And how interpret them?

Upvotes: 0

Views: 391

Answers (1)

Carmine Fazzi
Carmine Fazzi

Reputation: 1

I think maybe you are overthinking this one! Take a step back and think about what matters... the error. You have forecasted values and you have observed values. the difference tells you most of what you need to know when comparing across models. Basic measures like MSE, MPE, etc. should do fine. If you are looking to refine within a given model, I would recommend taking a look at the gbm documentation. For example, you can pass your gbm model object to summary(), to get the relative influence of each of your variables. Additionally, you can find a lot of information in the documentation, so if you haven't taken a look, I would recommend doing so! I have posted the link at the bottom.

-Carmine

gbm_documentation

Upvotes: -1

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