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Complete Guide to Parameter Tuning in Gradient Boosting (GBM) in Python

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@nirvgandhi wrote:

While searching for the steps or technique to optimize gradient boosting performance, I came across to the article mentioned in the link.

The article explains very well about the trade-off between few parameters and how to evaluate the performance. But what I feel is there is no where mention about the issue of overfitting. How can we minimize the issue of overfitting

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