pub enum SurrogateModel {
RandomForest {
n_trees: usize,
max_depth: Option<usize>,
},
GaussianProcess {
kernel_type: String,
},
NeuralNetwork {
hidden_layers: Vec<usize>,
},
LinearRegression {
regularization: Float,
},
}Expand description
Surrogate models for meta-learning
Variants§
RandomForest
Random Forest for hyperparameter prediction
GaussianProcess
Gaussian Process for uncertainty quantification
NeuralNetwork
Neural Network for complex patterns
Fields
LinearRegression
Linear model for simple relationships
Trait Implementations§
Source§impl Clone for SurrogateModel
impl Clone for SurrogateModel
Source§fn clone(&self) -> SurrogateModel
fn clone(&self) -> SurrogateModel
Returns a duplicate of the value. Read more
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
Performs copy-assignment from
source. Read moreAuto Trait Implementations§
impl Freeze for SurrogateModel
impl RefUnwindSafe for SurrogateModel
impl Send for SurrogateModel
impl Sync for SurrogateModel
impl Unpin for SurrogateModel
impl UnwindSafe for SurrogateModel
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
Source§impl<T> CloneToUninit for Twhere
T: Clone,
impl<T> CloneToUninit for Twhere
T: Clone,
Source§impl<T> IntoEither for T
impl<T> IntoEither for T
Source§fn into_either(self, into_left: bool) -> Either<Self, Self>
fn into_either(self, into_left: bool) -> Either<Self, Self>
Converts
self into a Left variant of Either<Self, Self>
if into_left is true.
Converts self into a Right variant of Either<Self, Self>
otherwise. Read moreSource§fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
Converts
self into a Left variant of Either<Self, Self>
if into_left(&self) returns true.
Converts self into a Right variant of Either<Self, Self>
otherwise. Read more