From 63ed89aadda2b1d9484d2f2d4ae05900207478a8 Mon Sep 17 00:00:00 2001 From: Lorenzo Date: Tue, 8 Nov 2022 12:17:04 +0000 Subject: [PATCH] minor fix --- src/linear/linear_regression.rs | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/linear/linear_regression.rs b/src/linear/linear_regression.rs index 7f6dfad..a5c7699 100644 --- a/src/linear/linear_regression.rs +++ b/src/linear/linear_regression.rs @@ -12,7 +12,7 @@ //! \\[\hat{\beta} = (X^TX)^{-1}X^Ty \\] //! //! the \\((X^TX)^{-1}\\) term is both computationally expensive and numerically unstable. An alternative approach is to use a matrix decomposition to avoid this operation. -//! smartcore uses [SVD](../../linalg/svd/index.html) and [QR](../../linalg/qr/index.html) matrix decomposition to find estimates of \\(\hat{\beta}\\). +//! `smartcore` uses [SVD](../../linalg/svd/index.html) and [QR](../../linalg/qr/index.html) matrix decomposition to find estimates of \\(\hat{\beta}\\). //! The QR decomposition is more computationally efficient and more numerically stable than calculating the normal equation directly, //! but does not work for all data matrices. Unlike the QR decomposition, all matrices have an SVD decomposition. //!