bigframes.ml.preprocessing.KBinsDiscretizer

class bigframes.ml.preprocessing.KBinsDiscretizer(n_bins: int = 5, strategy: Literal['uniform', 'quantile'] = 'quantile')

Bin continuous data into intervals.

Parameters:

• n_bins (int, default 5) – The number of bins to produce. Raises ValueError if n_bins < 2.

• strategy ({'uniform', 'quantile'}, default='quantile') – Strategy used to define the widths of the bins. ‘uniform’: All bins in each feature have identical widths. ‘quantile’: All bins in each feature have the same number of points.

Methods

__init__([n_bins, strategy])
fit(X[, y])	Fit the estimator.
fit_transform(X[, y])	Fit to data, then transform it.
get_params([deep])	Get parameters for this estimator.
to_gbq(model_name[, replace])	Save the transformer as a BigQuery model.
transform(X)	Discretize the data.