Meaninng
It's a machine learning technique
for optimizing the predictive value
of a model through successive steps
in the learning process.
Each iteration of the decision tree involves adjusting the values of the coefficients, weights, or biases applied to each of the input variables being used to predict the target value, with the goal of minimizing the loss function.
Without abbreviation
G: Gradient
B: Boosting
D: Decision
T: Tree
Process
- Compute the mean of the objective variable
- Compute the error
- Construct a decision tree
- Find new predictions using the ensemble
- Calculate the error again
- Repeat 3~5
- Make the final prediction