pub struct IsotonicRegression { /* private fields */ }Expand description
Monotone (non-decreasing) regression of y on a scalar x, predicting
by linear interpolation and clipping inputs to the training range, as
scikit-learn’s IsotonicRegression(out_of_bounds="clip").
Implementations§
Source§impl IsotonicRegression
impl IsotonicRegression
Sourcepub fn fit(
x: ArrayView1<'_, f64>,
y: ArrayView1<'_, f64>,
y_min: f64,
y_max: f64,
) -> Result<Self>
pub fn fit( x: ArrayView1<'_, f64>, y: ArrayView1<'_, f64>, y_min: f64, y_max: f64, ) -> Result<Self>
Fit with fitted values bounded to [y_min, y_max].
Trait Implementations§
Source§impl Clone for IsotonicRegression
impl Clone for IsotonicRegression
Auto Trait Implementations§
impl Freeze for IsotonicRegression
impl RefUnwindSafe for IsotonicRegression
impl Send for IsotonicRegression
impl Sync for IsotonicRegression
impl Unpin for IsotonicRegression
impl UnsafeUnpin for IsotonicRegression
impl UnwindSafe for IsotonicRegression
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
impl<ST, DT> CastableFrom<ST, Initialized, Initialized> for DT
impl<ST, DT> CastableFrom<ST, Uninit, Uninit> for DT
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