Struct linfa_svm::Svm

source · [−]

pub struct Svm<F: Float, T> {
    pub alpha: Vec<F>,
    pub rho: F,
    /* private fields */
}

Expand description

Fitted Support Vector Machines model

This is the result of the SMO optimizer and contains the support vectors, quality of solution and optionally the linear hyperplane.

Fields

alpha: Vec<F>rho: F

Implementations

impl<F: Float, L> Svm<F, L>

pub fn params() -> SvmParams<F, L>

impl<F: Float, T> Svm<F, T>

pub fn nsupport(&self) -> usize

Returns the number of support vectors

This function returns the number of support vectors which have an influence on the decision outcome greater than zero.

pub fn weighted_sum<D: Data<Elem = F>>(&self, sample: &ArrayBase<D, Ix1>) -> F

Sums the inner product of sample and every one of the support vectors.

Parameters

sample: the input sample

Returns

The sum of all inner products of sample and every one of the support vectors, scaled by their weight.

Panics

If the shape of sample is not compatible with the shape of the support vectors

Trait Implementations

impl<'a, F: Float, T> Display for Svm<F, T>

Display solution

In order to understand the solution of the SMO solver the objective, number of iterations and required support vectors are printed here.

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more

impl<F: Float, D: Data<Elem = F>> Predict<ArrayBase<D, Dim<[usize ; 1]>>, Pr> for Svm<F, Pr>

Predict a probability with a feature vector

fn predict(&self, data: ArrayBase<D, Ix1>) -> Pr

impl<'a, F: Float, D: Data<Elem = F>> Predict<ArrayBase<D, Dim<[usize ; 1]>>, bool> for Svm<F, bool>

Predict a probability with a feature vector

fn predict(&self, data: ArrayBase<D, Ix1>) -> bool

impl Predict<ArrayBase<OwnedRepr<f32>, Dim<[usize ; 1]>>, f32> for Svm<f32, f32>

Predict a probability with a feature vector

fn predict(&self, data: Array1<f32>) -> f32

impl Predict<ArrayBase<OwnedRepr<f64>, Dim<[usize ; 1]>>, f64> for Svm<f64, f64>

Predict a probability with a feature vector

fn predict(&self, data: Array1<f64>) -> f64

impl<'a> Predict<ArrayBase<ViewRepr<&'a f32>, Dim<[usize ; 1]>>, f32> for Svm<f32, f32>

Predict a probability with a feature vector

fn predict(&self, data: ArrayView1<'a, f32>) -> f32

impl<'a> Predict<ArrayBase<ViewRepr<&'a f64>, Dim<[usize ; 1]>>, f64> for Svm<f64, f64>

Predict a probability with a feature vector

fn predict(&self, data: ArrayView1<'a, f64>) -> f64

impl<F: Float, D: Data<Elem = F>> PredictInplace<ArrayBase<D, Dim<[usize ; 2]>>, ArrayBase<OwnedRepr<Pr>, Dim<[usize ; 1]>>> for Svm<F, Pr>

Predict a probability with a feature vector Classify observations

This function takes a number of features and predicts target probabilities that they belong to the positive class.

fn predict_inplace(&self, data: &ArrayBase<D, Ix2>, targets: &mut Array1<Pr>)

Predict something in place

fn default_target(&self, x: &ArrayBase<D, Ix2>) -> Array1<Pr>

Create targets that predict_inplace works with.

impl<F: Float, D: Data<Elem = F>> PredictInplace<ArrayBase<D, Dim<[usize ; 2]>>, ArrayBase<OwnedRepr<bool>, Dim<[usize ; 1]>>> for Svm<F, bool>

Classify observations

This function takes a number of features and predicts target probabilities that they belong to the positive class.

fn predict_inplace(&self, data: &ArrayBase<D, Ix2>, targets: &mut Array1<bool>)

Predict something in place

fn default_target(&self, x: &ArrayBase<D, Ix2>) -> Array1<bool>

Create targets that predict_inplace works with.

impl<D: Data<Elem = f32>> PredictInplace<ArrayBase<D, Dim<[usize ; 2]>>, ArrayBase<OwnedRepr<f32>, Dim<[usize ; 1]>>> for Svm<f32, f32>

Classify observations

This function takes a number of features and predicts target probabilities that they belong to the positive class.

fn predict_inplace<'a>(
    &'a self,
    data: &ArrayBase<D, Ix2>,
    targets: &mut Array1<f32>
)

Predict something in place

fn default_target(&self, x: &ArrayBase<D, Ix2>) -> Array1<f32>

Create targets that predict_inplace works with.

impl<D: Data<Elem = f64>> PredictInplace<ArrayBase<D, Dim<[usize ; 2]>>, ArrayBase<OwnedRepr<f64>, Dim<[usize ; 1]>>> for Svm<f64, f64>

Classify observations

This function takes a number of features and predicts target probabilities that they belong to the positive class.

fn predict_inplace<'a>(
    &'a self,
    data: &ArrayBase<D, Ix2>,
    targets: &mut Array1<f64>
)

Predict something in place

fn default_target(&self, x: &ArrayBase<D, Ix2>) -> Array1<f64>

Create targets that predict_inplace works with.

Auto Trait Implementations

impl<F, T> RefUnwindSafe for Svm<F, T> where
F: RefUnwindSafe,
T: RefUnwindSafe,

impl<F, T> Send for Svm<F, T> where
T: Send,

impl<F, T> Sync for Svm<F, T> where
T: Sync,

impl<F, T> Unpin for Svm<F, T> where
F: Unpin,
T: Unpin,

impl<F, T> UnwindSafe for Svm<F, T> where
F: UnwindSafe + RefUnwindSafe,
T: UnwindSafe,

Blanket Implementations

impl<T> Any for T where
T: 'static + ?Sized,

pub fn type_id(&self) -> TypeId

Gets the TypeId of self. Read more

impl<T> Borrow<T> for T where
T: ?Sized,

const: unstable · source

pub fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more

impl<T> BorrowMut<T> for T where
T: ?Sized,

const: unstable · source

pub fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more

impl<T> From<T> for T

const: unstable · source

pub fn from(t: T) -> T

Returns the argument unchanged.

impl<T, U> Into<U> for T where
U: From<T>,

const: unstable · source

pub fn into(self) -> U

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

impl<'a, F, D, DM, T, O> Predict<&'a ArrayBase<D, DM>, T> for O where
    D: Data<Elem = F>,
    DM: Dimension,
    O: PredictInplace<ArrayBase<D, DM>, T>,

pub fn predict(&self, records: &'a ArrayBase<D, DM>) -> T

impl<'a, F, R, T, S, O> Predict<&'a DatasetBase<R, T>, S> for O where
R: Records<Elem = F>,
O: PredictInplace<R, S>,

pub fn predict(&self, ds: &'a DatasetBase<R, T>) -> S

impl<F, D, E, T, O> Predict<ArrayBase<D, Dim<[usize ; 2]>>, DatasetBase<ArrayBase<D, Dim<[usize ; 2]>>, T>> for O where
    D: Data<Elem = F>,
    T: AsTargets<Elem = E>,
    O: PredictInplace<ArrayBase<D, Dim<[usize ; 2]>>, T>,

pub fn predict(
&self,
records: ArrayBase<D, Dim<[usize ; 2]>>
) -> DatasetBase<ArrayBase<D, Dim<[usize ; 2]>>, T>

impl<F, R, T, E, S, O> Predict<DatasetBase<R, T>, DatasetBase<R, S>> for O where
    R: Records<Elem = F>,
    S: AsTargets<Elem = E>,
    O: PredictInplace<R, S>,

pub fn predict(&self, ds: DatasetBase<R, T>) -> DatasetBase<R, S>

impl<T> ToString for T where
T: Display + ?Sized,

pub default fn to_string(&self) -> String

Converts the given value to a String. Read more

impl<T, U> TryFrom<U> for T where
U: Into<T>,

type Error = Infallible

The type returned in the event of a conversion error.

const: unstable · source

pub fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>

Performs the conversion.

impl<T, U> TryInto<U> for T where
U: TryFrom<T>,

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

The type returned in the event of a conversion error.

const: unstable · source

pub fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>

Performs the conversion.

impl<V, T> VZip<V> for T where
V: MultiLane<T>,

pub fn vzip(self) -> V