Enum FeatureKind 

pub enum FeatureKind {
    Mean,
    Variance,
    Skewness,
    Min,
    Max,
    Range,
    L1Norm,
    L2Norm,
    Histogram {
        bins: usize,
    },
}

Which feature to extract from a tensor slice.

Variants

Mean

Arithmetic mean: Σxᵢ / n (0.0 when empty)

Variance

Population variance: E[x²] − E[x]² (0.0 when empty)

Skewness

Standardised third central moment: E[(x−μ)³] / σ³ (0.0 when σ=0 or empty)

Min

Minimum element (0.0 when empty)

Max

Maximum element (0.0 when empty)

Range

Range: max − min (0.0 when empty)

L1Norm

L¹ norm: Σ|xᵢ|

L2Norm

L² norm: √(Σxᵢ²)

Histogram

Histogram: divide [min, max] into bins equal-width buckets and count elements. Produces bins values. When min == max every element falls in bucket 0.

Fields

bins: usize

Number of equal-width histogram bins.

Trait Implementations

impl Clone for FeatureKind

fn clone(&self) -> FeatureKind

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for FeatureKind

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

Formats the value using the given formatter.

impl Eq for FeatureKind

impl Hash for FeatureKind

fn hash<__H: Hasher>(&self, state: &mut __H)

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl PartialEq for FeatureKind

fn eq(&self, other: &FeatureKind) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for FeatureKind