pub enum LogisticRegressionAlgorithm {
MLE,
IRLS,
}Expand description
Algorithm to use for logistic regression.
Variants§
MLE
Maximum Likelihood Estimation using Algorithmic Adjoint Differentiation See: https://en.wikipedia.org/wiki/Logistic_regression#Maximum_likelihood_estimation_(MLE)
IRLS
Iterative Reweighted Least Squares From Wikipedia (https://en.wikipedia.org/wiki/Logistic_regression#Iteratively_reweighted_least_squares_(IRLS)): “”“ Binary logistic regression can, be calculated using iteratively reweighted least squares (IRLS), which is equivalent to maximizing the log-likelihood of a Bernoulli distributed process using Newton’s method. “”“
References: - Elements of Statistical Learning (Hastie, Tibshirani, Friedman 2009) - Machine Learning: A Probabilistic Perspective (Murphy, Kevin P. 2012)
Trait Implementations§
Source§impl Clone for LogisticRegressionAlgorithm
impl Clone for LogisticRegressionAlgorithm
Source§fn clone(&self) -> LogisticRegressionAlgorithm
fn clone(&self) -> LogisticRegressionAlgorithm
Returns a copy 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 moreimpl Copy for LogisticRegressionAlgorithm
Auto Trait Implementations§
impl Freeze for LogisticRegressionAlgorithm
impl RefUnwindSafe for LogisticRegressionAlgorithm
impl Send for LogisticRegressionAlgorithm
impl Sync for LogisticRegressionAlgorithm
impl Unpin for LogisticRegressionAlgorithm
impl UnwindSafe for LogisticRegressionAlgorithm
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Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
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fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
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Source§unsafe fn clone_to_uninit(&self, dst: *mut T)
unsafe fn clone_to_uninit(&self, dst: *mut T)
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Converts
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Source§impl<SS, SP> SupersetOf<SS> for SPwhere
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fn from_subset(element: &SS) -> SP
The inclusion map: converts
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The inverse inclusion map: attempts to construct
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fn from_subset(element: &SS) -> SP
The inclusion map: converts
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