API reference

The API reference provides an overview of all public functions in gwlearn.

Base classes

Base classes allow creation of geographically weighted versions of scikit-learn estimators.

BaseClassifier(model, *[, bandwidth, fixed, ...])

Generic geographically weighted classification meta-estimator.

BaseRegressor(model, *[, bandwidth, fixed, ...])

Generic geographically weighted regression meta-estimator.

Linear models

Implementation of linear models with access to relevant attributes (e.g. local coefficients).

GWLinearRegression([bandwidth, fixed, ...])

Geographically weighted linear regression

GWLogisticRegression([bandwidth, fixed, ...])

Geographically weighted logistic regression

Ensemble models

Implementation of linear models with access to relevant attributes (e.g. local feature importance).

GWGradientBoostingClassifier(*[, bandwidth, ...])

Geographically weighted gradient boosting classifier.

GWGradientBoostingRegressor(*[, bandwidth, ...])

Geographically weighted gradient boosting regressor.

GWRandomForestClassifier(*[, bandwidth, ...])

Geographically weighted random forest classifier.

GWRandomForestRegressor(*[, bandwidth, ...])

Geographically weighted random forest regressor.

Tooling to determine the optimal bandwidths of geographically weighted models.

BandwidthSearch(model, *[, fixed, kernel, ...])

Optimal bandwidth search for geographically weighted estimators.