watex.methods.hydro.MXS.predictNGA#

MXS.predictNGA(n_components=2, return_label=False, **NGA_kws)[source]#

Predicts Naive Group of Aquifer from Hydro-Log data.

Parameters:

n_components (int, default=2) – Number of dimension to preserve. If`n_components` is ranged between float 0. to 1., it indicates the number of variance ratio to preserve. If None as default value the number of variance to preserve is 95%.
return_label (bool,default=False) – If True, return the NGA label predicted, otherwise return MXS instanciated object. if False, NGA label can be fetch using the attribute watex.hydro.MXS.yNGA_
NGA_kws (dict,) – keyword argument passed to watex.utils.predict_NGA_labels()

Returns:

yNGA_ or self – MXS instanciated object.

Return type:

arraylike-1d of naive group of aquifer or

Example

>>> from watex.datasets import load_hlogs
>>> from watex.methods.hydro import MXS
>>> hdata = load_hlogs ().frame
>>> # drop the 'remark' columns since there is no valid data
>>> hdata.drop (columns ='remark', inplace=True)
>>> mxs =MXS (kname ='k').fit(hdata) # specify the 'k' column
>>> y_pred = mxs.predictNGA(return_label=True )
>>> y_pred [-12:]
Out[52]: array([1, 3, 1, 3, 3, 3, 3, 1, 3, 3, 3, 3])