miniboosts 0.2.1

MiniBoosts: A collection of boosting algorithms written in Rust 🦀
Documentation 
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/// Loss functions available to Neural networks.
#[derive(Clone, Copy)]
pub enum NNLoss {
    /// Least squared loss
    L2,

    /// Cross-entropy loss
    CrossEntropy,
}


impl NNLoss {
    /// Returns a differentiate for a given minibatch.
    #[inline(always)]
    pub fn diff(&self, p: Vec<f64>, y: Vec<f64>) -> Vec<f64> {
        match self {
            Self::L2 => l2_diff(p, y),
            Self::CrossEntropy => cross_entropy_diff(p, y),
        }
    }
}


#[inline(always)]
fn l2_diff(p: Vec<f64>, y: Vec<f64>) -> Vec<f64> {
    p.into_iter()
        .zip(y)
        .map(|(pi, yi)| pi - yi)
        .collect()
}

#[inline(always)]
fn cross_entropy_diff(p: Vec<f64>, y: Vec<f64>) -> Vec<f64> {
    p.into_iter()
        .zip(y)
        .map(|(pi, yi)| pi - yi)
        .collect()
}