oraclesai.classification.GWRClassifier

class GWRClassifier(spatial_weights_definition=None, bandwidth=None, fixed=True)

Geographical Weighted Regression for binary classification. A logistic model is trained for each observation by including the target and explanatory variables from the observations falling within a specified bandwidth.

Parameters:

• spatial_weights_definition – SpatialWeightsDefinition, default=None. Spatial relationship specification.

• bandwidth – scalar, default=None. Bandwidth value consisting of either a distance or K nearest neighbors. If the bandwidth is provided, it overrides the parameter spatial_weights_definition according to fixed.

• fixed – boolean, default=True. Works only when bandwidth is defined. If True it uses DistanceBandWeightsDefinition as spatial weights; otherwise, it uses KNNWeightsDefinition.

Methods

__init__([spatial_weights_definition, ...])
fit(X, y[, geometries, crs])	Search for the bandwidth and fits a binomial GWR model with the given data.
get_params([deep])	Get parameters for this estimator.
predict(X[, geometries])	Evaluates the binomial GWR model with the given data.
score(X, y[, sample_weight, geometries])	Returns the accuracy of the model.
set_params(**params)	Set the parameters of this estimator.

Attributes

betas	returns: A 2D-array with the estimated parameters (n x k) for the binomial GWR model
k	returns: The number of variables for which coefficients are estimated (including the
model_type	returns: The type of the classification model
predy	returns: An array with the predictions for the training data
summary	returns: A summary of the trained model
u	returns: An array with the residuals of the trained binomial GWR model