skdownscale.pointwise_models.QuantileMapper¶

class skdownscale.pointwise_models.QuantileMapper(detrend=False, lt_kwargs=None, qt_kwargs=None)[source]¶

Transform features using quantile mapping.

Parameters:

detrend (boolean, optional) – If True, detrend the data before quantile mapping and add the trend back after transforming. Default is False.
lt_kwargs (dict, optional) – Dictionary of keyword arguments to pass to the LinearTrendTransformer
qm_kwargs (dict, optional) – Dictionary of keyword arguments to pass to the QuantileMapper

x_cdf_fit_¶

QuantileTranform for fit(X)

Methods

`__init__`([detrend, lt_kwargs, qt_kwargs])
`fit`(X[, y])	Fit the quantile mapping model.
`fit_transform`(X[, y])	Fit to data, then transform it.
`get_metadata_routing`()	Get metadata routing of this object.
`get_params`([deep])	Get parameters for this estimator.
`set_output`(*[, transform])	Set output container.
`set_params`(**params)	Set the parameters of this estimator.
`transform`(X)	Perform the quantile mapping.

fit(X, y=None)[source]¶

Fit the quantile mapping model.

Parameters:: X (array-like, shape [n_samples, n_features]) – Training data

transform(X)[source]¶

Perform the quantile mapping.