oraclesai.regression.SpatialLagRegressor

class SpatialLagRegressor(spatial_weights_definition=None)

The Spatial Lag regression model considers spatial dependence over the target variable, meaning that the value of a region’s target variable is related to its neighbors’ target variable. The Spatial Lag model includes the spatial lag of the dependent variable into the linear equation; this results in an extra parameter associated with the spatial lag of the dependent variable

Parameters:

spatial_weights_definition – SpatialWeightsDefinition, default=None. Specifies the spatial relationship among neighbors.

Methods

__init__([spatial_weights_definition])
fit(X, y[, geometries, crs, spatial_weights])	Trains the model using the training dataset.
get_params([deep])	Get parameters for this estimator.
predict(X[, geometries])	Estimates the target variable for the given data.
score(X, y[, sample_weight, geometries])	Returns the value of the regression score function or R-Squared.
set_params(**params)	Set the parameters of this estimator.

Attributes

betas	returns: An array with the estimated parameters of the trained model
diagnostics	returns: A SpatialDiagnostics instance containing statistics of the trained model. If no
k	returns: The number of variables for which coefficients are estimated (including the
model_type	returns: The regression model defined
predy	returns: An array with the predictions for the training data
summary	returns: The summary of the trained model
u	returns: An array with the residuals of the trained model