zoom.pls_tool.get_vip2

zoom.pls_tool.get_vip2(mod: sklearn.cross_decomposition._pls.PLSRegression, X: numpy.ndarray, y: numpy.ndarray) → numpy.ndarray[source]

Compute variance explained for each PLS-R component.

Parameters:

mod (sklearn.cross_decomposition._pls.PLSRegression) – PLS-R model fitted to X and y.
y (X &) – Independent and dependent variables of PLS-R model.

Returns:

vip – Variable importance in projection index for independent variables.

Return type:

np.ndarray with shape (X.shape[1],)

References

Mahieu, B., Qannari, E. M. & Jaillais, B. Extension and significance testing of Variable Importance in Projection (VIP) indices in Partial Least Squares regression and Principal Components Analysis. Chemom. Intell. Lab. Syst. 242, 104986 (2023).