Examining Bayesian Additive Regression Trees for Unemployment Rate Prediction
Code in this example can be found on my github Introduction Gradient boosting methods are commonly used in the Machine Learning field. It’s a rather straight forward process as it utilized “tree boosting” optimization methods by combining random forest algorithms with a learning rate. Gradient boosting algorithms are seeking to minimize an objective function. O ij = ∑ i = 1 I loss ( y i , y ~ i ) ⏟ error term + ∑ j = 1 J λ ( T j ) ⏟ regularization term Most common machine learning algorithms are using a similar basic objective function which is based on a frequentist approach towards statistics....