See: Description
Interface | Description |
---|---|
AbstractRegressionModel |
Interface for all regression models.
|
Class | Description |
---|---|
AbstractNonlinearRegression |
Abstract class for models that fit terms using non-linear regression.
|
AbstractParsedNonlinearRegression |
Superclass of
AbstractNonlinearRegression -based models which parse the equation
of interest from text input. |
BaseRegression |
Base class for all regression models.
|
ClassificationRegression |
Use a classification algorithm to perform regression.
|
CompositeRegression |
Ensemble of regression models.
|
GuessMeanRegression |
Always guess the mean of the values provided during training.
|
LASSORegression |
This class enables regression using the LASSO algorithm, as described by
this page.
|
LinearCorrectedRegression |
Apply a linear correction to results from another model.
|
MetallurgicalHeuristicRegression |
Estimate formation energy for ternary+ alloys using a metallurgical heuristic.
|
MixingRuleRegression |
Predicts the class of a
CompositionEntry based on the composition-weighted mean. |
MultiObjectiveRegression |
Employs multiple models, each designed to predict a different property that composes
the class variable.
|
MultiPropertyRegression |
Extension of MultiObjectiveEntryRanker where one does not care
about the class variable.
|
NonlinearRegressionExpr |
Performs non-linear regression on a function supplied as a string.
|
PolynomialRegression |
Performs linear regression using all attributes in a Dataset raised to integer
exponents.
|
RandomGuessRegression |
Randomly assign class values.
|
ScikitLearnRegression |
Uses Scikit-learn to train a regression model.
|
SingleGuessRegression |
Guess a single, user-specified value for the class variable of all entries.
|
SplitRegression |
Abstract class for models that use multiple submodels.
|
StagedRegression |
Composite regression where the error signal from a model is used to train the next.
|
WekaRegression |
Implementation of
WekaModel for regression purposes. |