Gradient Boosting Regressor Step
Calculus & Optimization DS practice problem on Onlearn.
Difficulty: hard.
Topics: Understanding Gradient Boosting Regression Iteration, Pseudo-residual calculation, Negative gradient of MSE, Boosting iteration logic, Additive modeling, Learning rate application, Numerical Optimization, Supervised Learning, Calculus, Ensemble Methods, Statistical Learning Theory, Gradient Descent, Loss Function Minimization, Functional Gradient Boosting, Residual Analysis, Weak Learner Interaction.
Implement a single step of the Gradient Boosting Regressor. Given the current predictions (y pred) and the true target values (y true), calculate the pseudo residuals and return them as the target for the next weak learner. Assume a Mean Squared Error loss function.