feat: Make SerDe optional
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@@ -62,14 +62,15 @@
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//! <script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
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use std::fmt::Debug;
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use serde::{Deserialize, Serialize};
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#[cfg(feature = "serde")] use serde::{Deserialize, Serialize};
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use crate::api::{Predictor, SupervisedEstimator};
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use crate::error::Failed;
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use crate::linalg::Matrix;
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use crate::math::num::RealNumber;
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#[derive(Serialize, Deserialize, Debug, Clone)]
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#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
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#[derive(Debug, Clone)]
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/// Approach to use for estimation of regression coefficients. QR is more efficient but SVD is more stable.
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pub enum LinearRegressionSolverName {
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/// QR decomposition, see [QR](../../linalg/qr/index.html)
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@@ -79,14 +80,16 @@ pub enum LinearRegressionSolverName {
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}
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/// Linear Regression parameters
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#[derive(Serialize, Deserialize, Debug, Clone)]
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#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
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#[derive(Debug, Clone)]
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pub struct LinearRegressionParameters {
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/// Solver to use for estimation of regression coefficients.
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pub solver: LinearRegressionSolverName,
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}
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/// Linear Regression
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#[derive(Serialize, Deserialize, Debug)]
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#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
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#[derive(Debug)]
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pub struct LinearRegression<T: RealNumber, M: Matrix<T>> {
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coefficients: M,
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intercept: T,
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