oraclesai.preprocessing.CategoricalLagTransformer

class CategoricalLagTransformer(spatial_weights_definition=None)

The categorical lag is used for categorical variables and represents the most common value in the neighborhood. For example, given a feature representing the property type; the categorical lag is the most common property in the surroundings

Parameters:

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

Methods

__init__([spatial_weights_definition])
fit(X[, y, geometries, spatial_weights])	Calculates the spatial weights of the training data using the algorithm associated with the parameter spatial_weights_definition and the geometry column.
fit_transform(X[, y, geometries])	Fit to data, then transform it.
get_params([deep])	Get parameters for this estimator.
set_params(**params)	Set the parameters of this estimator.
transform(X[, y, geometries, ...])	Returns the most common value from each location's neighbors; by defining the parameter use_fit_lag, it can use the neighbors from the training set, or the data passed into the transform method; the output is a NumPy array.