discrimintools.fviz_plsr

discrimintools.fviz_plsr(obj, element='ind', **kwargs)

Visualize Partial Least Squares Regression (CPLS, PLSDA, PLSLDA, PLSLOGIT)

fviz_plsr provides plotnine based elegant visualization of CPLS, PLSDA, PLSLDA and PLSLOGIT outputs.

Parameters:

• obj (class) – An object of class CPLS, PLSDA, PLSLDA, PLSLOGIT.

• element (str, default = ‘ind’) – The element to plot from the output, possible values:

  • ‘ind’ for the individuals graphs

  • ‘var’ for the variables graphs (= Correlation circle)

  • ‘dist’ for the distance graphs

• **kwargs – further arguments passed to or from other methods

Returns:

p – A object of class ggplot.

Return type:

class

See also

fviz_plsr_ind

Visualize Partial Least Squares Regression (CPLS, PLSDA, PLSLDA, PLSLOGIT) - Graph of individuals.

fviz_plsr_var

Visualize Partial Least Squares Regression (CPLS, PLSDA, PLSLDA, PLSLOGIT) - Graph of variables.

fviz_dist

Visualize distance between barycenter.

Examples

>>> from discrimintools.datasets import load_dataset
>>> from discrimintools import CPLS, fviz_plsr
>>> D = load_dataset("breast") # load traning data
>>> y, X = D["Class"], D.drop(columns=["Class"]) # split into X and y
>>> clf = CPLS()
>>> clf.fit(X,y)
CPLS()

Graph of individuals…

>>> p = fviz_plsr(clf, "ind") # graph of individuals
>>> print(p)

Fig. 17 Graph of individuals - CPLS

Graph of variables…

>>> p = fviz_cpls(clf, "var") # graph of variables
>>> print(p)

Fig. 18 Graph of variables - CPLS

Distance between class barycenter.

>>> p = fviz_cpls(clf, "dist") # graph of distance
>>> print(p)

Fig. 19 Distance between barycenter - CPLS