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AggregationModel

Enum AggregationModel 

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pub enum AggregationModel {
    DirectRating {
        default_rating: f64,
    },
    Elo {
        initial_rating: f64,
        k_factor: f64,
    },
    BradleyTerry {
        initial_strength: f64,
        optimizer: BradleyTerryOptimizer,
    },
    BradleyTerrySimple {
        initial_strength: f64,
        learning_rate: f64,
        iterations: usize,
    },
    ImplicitRanking {
        selected_bonus: f64,
        not_selected_penalty: f64,
        base_fitness: f64,
    },
}
Expand description

Aggregation model for converting user feedback to fitness

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DirectRating

Direct rating average

Simply averages all ratings received for each candidate. Uses default_rating for candidates with no ratings.

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§default_rating: f64

Default rating for unevaluated candidates

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Elo

Elo rating system

Classic chess-style rating from pairwise comparisons. Good for transitive preference modeling.

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§initial_rating: f64

Initial rating for new candidates

§k_factor: f64

K-factor controlling rating volatility

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BradleyTerry

Bradley-Terry model

Maximum likelihood estimation for pairwise comparison data. Provides more statistically principled estimates than Elo. Now supports proper MLE with Newton-Raphson or MM algorithms.

Fields

§initial_strength: f64

Initial strength parameter

§optimizer: BradleyTerryOptimizer

Optimizer configuration (Newton-Raphson or MM)

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BradleyTerrySimple

Legacy Bradley-Terry model (for backward compatibility)

Uses the simplified iterative MM approach from earlier versions.

Fields

§initial_strength: f64

Initial strength parameter

§learning_rate: f64

Learning rate for iterative updates

§iterations: usize

Number of iterations

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ImplicitRanking

Implicit ranking from batch selections

Assigns bonuses to selected candidates and penalties to non-selected candidates in each batch.

Fields

§selected_bonus: f64

Fitness bonus for being selected

§not_selected_penalty: f64

Fitness penalty for not being selected

§base_fitness: f64

Base fitness for all candidates

Trait Implementations§

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impl Clone for AggregationModel

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fn clone(&self) -> AggregationModel

Returns a duplicate of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for AggregationModel

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

Formats the value using the given formatter. Read more
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impl Default for AggregationModel

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fn default() -> Self

Returns the “default value” for a type. Read more
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impl<'de> Deserialize<'de> for AggregationModel

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fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>
where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer. Read more
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impl Serialize for AggregationModel

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fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>
where __S: Serializer,

Serialize this value into the given Serde serializer. Read more

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

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fn borrow(&self) -> &T

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

Mutably borrows from an owned value. Read more
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impl<T> CloneToUninit for T
where T: Clone,

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unsafe fn clone_to_uninit(&self, dest: *mut u8)

🔬This is a nightly-only experimental API. (clone_to_uninit)
Performs copy-assignment from self to dest. Read more
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impl<T> From<T> for T

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fn from(t: T) -> T

Returns the argument unchanged.

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fn into(self) -> U

Calls U::from(self).

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fn into_either(self, into_left: bool) -> Either<Self, Self>

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fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
where F: FnOnce(&Self) -> bool,

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impl<T> Pointable for T

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const ALIGN: usize

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type Init = T

The type for initializers.
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unsafe fn init(init: <T as Pointable>::Init) -> usize

Initializes a with the given initializer. Read more
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fn to_subset(&self) -> Option<SS>

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