algorithm_parameters

Description

Outlines a collection of hyperparameters specific to the chosen algorithm. These parameters control various aspects of the algorithm's behavior and performance, such as learning rate, number of trees (in tree-based models), or regularization terms. Proper tuning of these parameters is essential for optimizing the model's accuracy and efficiency.

Steps impacted

training

Example

date_col: Date_Chargement
algo_type: regression
algo_name: xgboost
algorithm_parameters:
  n_estimators: 150
  max_depth: 4