Struct Tversky 

pub struct Tversky {
    pub alpha: f64,
    pub beta: f64,
    pub bias: f64,
}

Tversky similarity is a generalization of SorensenDice and Jaccard.

Fields

alpha: f64

α, the weight of the first sequence (the “prototype”).

beta: f64

β, the weight of the second sequence (the “variant”).

bias: f64

The symmetric Tversky index bias parameter.

Trait Implementations

impl Algorithm<f64> for Tversky

fn for_iter<C, E>(&self, s1: C, s2: C) -> Result<f64>

where C: Iterator<Item = E>, E: Eq + Hash,

Calculate distance/similarity for iterators.

fn for_vec<E>(&self, s1: &[E], s2: &[E]) -> Result<R>

where E: Eq + Hash,

Calculate distance/similarity for vectors.

fn for_str(&self, s1: &str, s2: &str) -> Result<R>

Calculate distance/similarity for strings.

fn for_words(&self, s1: &str, s2: &str) -> Result<R>

Calculate distance/similarity for words in strings.

fn for_bigrams(&self, s1: &str, s2: &str) -> Result<R>

Calculate distance/similarity for bigrams in strings.

impl Default for Tversky

fn default() -> Self

Returns the “default value” for a type.