[][src]Enum opencv::ml::Boost_Types

#[repr(C)]pub enum Boost_Types {
    DISCRETE,
    REAL,
    LOGIT,
    GENTLE,
}

Boosting type. Gentle AdaBoost and Real AdaBoost are often the preferable choices.

Variants

DISCRETE

Discrete AdaBoost.

REAL

Real AdaBoost. It is a technique that utilizes confidence-rated predictions and works well with categorical data.

LOGIT

LogitBoost. It can produce good regression fits.

GENTLE

Gentle AdaBoost. It puts less weight on outlier data points and for that reason is often good with regression data.

Trait Implementations

impl Clone for Boost_Types[src]

impl Copy for Boost_Types[src]

impl Debug for Boost_Types[src]

impl PartialEq<Boost_Types> for Boost_Types[src]

impl StructuralPartialEq for Boost_Types[src]

Auto Trait Implementations

Blanket Implementations

impl<T> Any for T where
    T: 'static + ?Sized
[src]

impl<T> Borrow<T> for T where
    T: ?Sized
[src]

impl<T> BorrowMut<T> for T where
    T: ?Sized
[src]

impl<T> From<T> for T[src]

impl<T, U> Into<U> for T where
    U: From<T>, 
[src]

impl<T> ToOwned for T where
    T: Clone
[src]

type Owned = T

The resulting type after obtaining ownership.

impl<T, U> TryFrom<U> for T where
    U: Into<T>, 
[src]

type Error = Infallible

The type returned in the event of a conversion error.

impl<T, U> TryInto<U> for T where
    U: TryFrom<T>, 
[src]

type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.