def __init__(self, method='yeo-johnson', standardize=True, copy=True):
self._hyperparams = {
'method': method,
'standardize': standardize,
'copy': copy
}
self._wrapped_model = Op(**self._hyperparams)
def __init__(self, with_centering=True, with_scaling=True, quantile_range=(25.0, 75.0), copy=True):
self._hyperparams = {
'with_centering': with_centering,
'with_scaling': with_scaling,
'quantile_range': quantile_range,
'copy': copy}
self._wrapped_model = Op(**self._hyperparams)
def __init__(self, copy=True, with_mean=True, with_std=True):
self._hyperparams = {
'copy': copy,
'with_mean': with_mean,
'with_std': with_std
}
self._wrapped_model = Op(**self._hyperparams)
def __init__(self, n_quantiles=1000, output_distribution='uniform', ignore_implicit_zeros=False, subsample=100000, random_state=None, copy=True):
self._hyperparams = {
'n_quantiles': n_quantiles,
'output_distribution': output_distribution,
'ignore_implicit_zeros': ignore_implicit_zeros,
'subsample': subsample,
'random_state': random_state,
'copy': copy}
self._wrapped_model = Op(**self._hyperparams)
def __init__(self, feature_range=(0, 1), copy=True):
self._hyperparams = {
'feature_range': feature_range,
'copy': copy}
self._wrapped_model = Op(**self._hyperparams)
def __init__(self, norm='l2', copy=True):
self._hyperparams = {'norm': norm, 'copy': copy}
self._wrapped_model = Op(**self._hyperparams)
def __init__(self, threshold=0.0, copy=True):
self._hyperparams = {'threshold': threshold, 'copy': copy}
self._wrapped_model = Op(**self._hyperparams)
def __init__(self, degree=2, interaction_only=False, include_bias=True):
self._hyperparams = {
'degree': degree,
'interaction_only': interaction_only,
'include_bias': include_bias}
self._wrapped_model = Op(**self._hyperparams)
def __init__(self, copy=True):
self._hyperparams = {'copy': copy}
self._wrapped_model = Op(**self._hyperparams)