66 lines
1.7 KiB
Rust
66 lines
1.7 KiB
Rust
use serde::{Deserialize, Serialize};
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use crate::linalg::BaseVector;
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use crate::math::num::FloatExt;
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#[derive(Serialize, Deserialize, Debug)]
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pub struct Precision {}
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impl Precision {
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pub fn get_score<T: FloatExt, V: BaseVector<T>>(&self, y_true: &V, y_pred: &V) -> T {
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if y_true.len() != y_pred.len() {
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panic!(
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"The vector sizes don't match: {} != {}",
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y_true.len(),
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y_pred.len()
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);
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}
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let mut tp = 0;
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let mut p = 0;
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let n = y_true.len();
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for i in 0..n {
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if y_true.get(i) != T::zero() && y_true.get(i) != T::one() {
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panic!(
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"Precision can only be applied to binary classification: {}",
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y_true.get(i)
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);
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}
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if y_pred.get(i) != T::zero() && y_pred.get(i) != T::one() {
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panic!(
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"Precision can only be applied to binary classification: {}",
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y_pred.get(i)
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);
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}
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if y_pred.get(i) == T::one() {
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p += 1;
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if y_true.get(i) == T::one() {
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tp += 1;
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}
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}
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}
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T::from_i64(tp).unwrap() / T::from_i64(p).unwrap()
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}
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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#[test]
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fn precision() {
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let y_true: Vec<f64> = vec![0., 1., 1., 0.];
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let y_pred: Vec<f64> = vec![0., 0., 1., 1.];
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let score1: f64 = Precision {}.get_score(&y_pred, &y_true);
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let score2: f64 = Precision {}.get_score(&y_pred, &y_pred);
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assert!((score1 - 0.5).abs() < 1e-8);
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assert!((score2 - 1.0).abs() < 1e-8);
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}
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}
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