moonalloy 0.3.2

The oxidized scientific computing library for the 21st century
Documentation 
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use crate::linalg::array::Array;
use crate::machine_learning::model::Model;

///
pub struct SimpleLinearRegression {
    slope: f64,
    feature: f64,
}

impl SimpleLinearRegression {
    pub fn new() -> Self {
        SimpleLinearRegression {
            slope: 0.0,
            feature: 0.0,
        }
    }

    pub fn from(slope: f64, feature: f64) -> Self {
        SimpleLinearRegression { slope, feature }
    }

    pub fn get_slope(&self) -> f64 {
        self.slope
    }

    pub fn get_feature(&self) -> f64 {
        self.feature
    }
}

impl Model for SimpleLinearRegression {
    fn predict(&mut self, observed_xs: Array) -> Array {
        observed_xs.scalar_mult(self.slope).scalar_add(self.feature)
    }

    fn optimize(&mut self, xs: Array, ys: Array) {
        self.slope = xs
            .scalar_sub(xs.average())
            .mult(&ys.scalar_sub(ys.average()))
            .sum()
            / xs.scalar_sub(xs.average())
                .mult(&xs.scalar_sub(xs.average()))
                .sum();
        self.feature = ys.average() - (self.slope * xs.average());
    }
}