PetscRegressor#
Abstract PETSc object that manages regression and classification problems
Synopsis#
typedef struct _p_PetscRegressor *PetscRegressor;
Notes#
For linear problems PetscRegressor supports ordinary least squares, lasso, and ridge regression using the PetscRegressorType of PETSCREGRESSORLINEAR
and PetscRegressorLinearType of REGRESSOR_LINEAR_OLS, REGRESSOR_LINEAR_LASSO, and REGRESSOR_LINEAR_RIDGE.
We have slightly abused the term “regressor” in the naming of this component of PETSc.
Statisticians would say that we are doing “regression”, and a “regressor”, in this context, strictly means an
independent (or “predictor”) variable in the regression analysis. However, “regressor” has taken on an informal
meaning in the machine-learning community of something along the lines of “algorithm or implementation used to fit
a regression model”. Examples are MLPRegressor (multi-layer perceptron regressor) or RandomForestRegressor
from the scikit-learn toolkit (which is itself not consistent about the use of the term “regressor”, since it has a
LinearRegression component instead of a LinearRegressor component).
See Also#
PetscRegressorCreate(), PetscRegressorLinearType, PetscRegressorSetType(), PetscRegressorType, PetscRegressorDestroy(),
PETSCREGRESSORLINEAR, PetscRegressorLinearType, REGRESSOR_LINEAR_OLS, REGRESSOR_LINEAR_LASSO, REGRESSOR_LINEAR_RIDGE.
Level#
beginner
Location#
Implementations#
_p_PetscRegressor in include/petsc/private/regressorimpl.h
PetscRegressor_Linear in src/ml/regressor/impls/linear/linearimpl.h
Index of all PetscRegressor routines
Table of Contents for all manual pages
Index of all manual pages