miniboosts 0.3.6

MiniBoosts: A collection of boosting algorithms written in Rust 🦀
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31

//! The core library for the weak learner in the boosting protocol.
use crate::Sample;

/// An interface that returns a struct of type `Hypothesis`.
pub trait WeakLearner {
    /// Returned hypothesis generated by `self`.
    type Hypothesis;


    /// Defines the name of weak-learning algorithm.
    fn name(&self) -> &str {
        "Not specified"
    }


    /// Returns the information of boosting algorithm as `String`.
    /// This method is used for [`Logger`](crate::research::Logger).
    /// By default, this method returns `None`.
    fn info(&self) -> Option<Vec<(&str, String)>> {
        None
    }


    /// For classification, `WeakLearner::produce`
    /// outputs an instance of `Classifier` trait
    /// that achieves high accuracy
    /// on the given distribution `dist`.
    fn produce(&self, sample: &Sample, dist: &[f64])
        -> Self::Hypothesis;
}