Shrinkage is a hyperparameter in gradient boosting that controls how strongly each new learner contributes to the ensemble. Lower shrinkage values act like a smaller learning rate and can reduce overfitting, often at the cost of requiring more boosting iterations.
A hyperparameter in gradient boosting that controls overfitting. Shrinkage in gradient boosting is analogous to learning rate in gradient descent. Shrinkage is a decimal value between 0.0 and 1.0. A lower shrinkage value reduces overfitting more than a larger shrinkage value.