Can you explain to me the parameter gamma in XGBoost algorithm? What is its impact on the model's perfomance?
The Parameter gamma in XGBoost Algorithm stands for Exponentiation Growing Bias. It helps in controlling the rate of growth of weights during training and regularization process. The larger value of gamma results in faster convergence but at a cost of higher risk of overfitting. A good choice of gamma depends on various factors such as size of dataset, number of features etc. To determine an appropriate value of gamma, one can experiment with different values and observe how it affects the performance of the model.