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//! # Common Interfaces and API
//!
//! This module provides interfaces and uniform API with simple conventions
//! that are used in other modules for supervised and unsupervised learning.
use crate::error::Failed;
/// An estimator for unsupervised learning, that provides method `fit` to learn from data
pub trait UnsupervisedEstimator<X, P> {
/// Fit a model to a training dataset, estimate model's parameters.
/// * `x` - _NxM_ matrix with _N_ observations and _M_ features in each observation.
/// * `parameters` - hyperparameters of an algorithm
fn fit(x: &X, parameters: P) -> Result<Self, Failed>
where
Self: Sized,
P: Clone;
}
/// An estimator for supervised learning, , that provides method `fit` to learn from data and training values
pub trait SupervisedEstimator<X, Y, P> {
/// Fit a model to a training dataset, estimate model's parameters.
/// * `x` - _NxM_ matrix with _N_ observations and _M_ features in each observation.
/// * `y` - target training values of size _N_.
/// * `parameters` - hyperparameters of an algorithm
fn fit(x: &X, y: &Y, parameters: P) -> Result<Self, Failed>
where
Self: Sized,
P: Clone;
}
/// Implements method predict that estimates target value from new data
pub trait Predictor<X, Y> {
/// Estimate target values from new data.
/// * `x` - _NxM_ matrix with _N_ observations and _M_ features in each observation.
fn predict(&self, x: &X) -> Result<Y, Failed>;
}
/// Implements method transform that filters or modifies input data
pub trait Transformer<X> {
/// Transform data by modifying or filtering it
/// * `x` - _NxM_ matrix with _N_ observations and _M_ features in each observation.
fn transform(&self, x: &X) -> Result<X, Failed>;
}