Gradient Boosted Models (iai_gbm)

Gradient boosting is a machine learning algorithm for building predictive models that helps minimize the bias error of the model. The gradient boosting model provided by integrate.ai is an HFL model that uses the sklearn implementation of HistGradientBoostingClassifier for classifier tasks and HistGradientBoostingRegresssor for regression tasks.

Example Model Configuration

model_config = {
    "strategy": {
        "name": "HistGradientBoosting",
        "params": {}
    },
    "model": {
        "params": {
            "max_depth": 4, 
            "learning_rate": 0.05,
            "random_state": 23, 
            "max_bins": 128,
            "sketch_relative_accuracy": 0.001,
        }
    },

    "ml_task": {"type": "classification", "params": {}}, 
    
    "save_best_model": {
        "metric": None,
        "mode": "min"
    },
  }

For more information, see HFL Gradient Boosted Models (HFL-GBM).