# API Reference

Documentation for the Heuristics public interface.

## XGBoost

IAI.XGBoostClassifierType

Learner for training XGBoost models for classification problems.

The following parameters are supported (refer to the documentation for each):

IAI.XGBoostRegressorType

Learner for training XGBoost models for regression problems.

The following parameters are supported (refer to the documentation for each):

IAI.write_boosterFunction
write_booster(filepath, lnr::XGBoostLearner)

Write the internal booster saved in lnr to filepath.

This can be used to open the trained XGBoost model using the XGBoost Python wrapper in order to conduct a SHAP analysis.

If filepath ends in ".json" the booster will be written in JSON format, otherwise an internal XGBoost binary format is used.

Warning

This output file cannot be loaded back into the IAI interface. Use write_json to save the entire learner if you want to be able to read it back in future.

## GLMNet

IAI.GLMNetCVRegressorType

Learner for training GLMNet models for regression problems with cross-validation.

The following parameters are supported (refer to the documentation for each):

IAI.get_num_fitsMethod
get_num_fits(lnr::GLMNetCVRegressor)

Returns the number of fits along the path in lnr.

IAI.predictMethod
predict(lnr::GLMNetCVRegressor, X::FeatureInput)

Returns the prediction made by the best fit on the path for lnr for each point in the data X.

predict(lnr::GLMNetCVRegressor, X::FeatureInput, fit_index::Integer)

Returns the prediction made by the fit at fit_index on the path for lnr for each point in the data X.

IAI.scoreMethod
score(lnr::GLMNetCVRegressor, X::FeatureInput, y::TargetInput...;
keyword_arguments...)

Calculates the score for the best fit on the path for lnr on data X and y.

score(lnr::GLMNetCVRegressor, X::FeatureInput, y::TargetInput...;
fit_index::Integer, keyword_arguments...)

Calculates the score for the fit at fit_index on the path for lnr on data X and y.

IAI.get_prediction_weightsMethod
get_prediction_weights(lnr::GLMNetCVRegressor)

Return the weights for each feature in the prediction made by the best fit on the path in lnr.

get_prediction_weights(lnr::GLMNetCVRegressor, fit_index::Integer)

Return the weights for each feature in the prediction made by the fit at fit_index on the path in lnr.

IAI.get_prediction_constantMethod
get_prediction_constant(lnr::GLMNetCVRegressor)

Return the constant term in the prediction made by the best fit on the path in lnr.

get_prediction_constant(lnr::GLMNetCVRegressor, fit_index::Integer)

Return the constant term in the prediction made by the fit at fit_index on the path in lnr.