From 5ce18bed7c06d86b56ec6fb23333afe3323cb417 Mon Sep 17 00:00:00 2001 From: jackfrued Date: Fri, 14 Feb 2025 14:01:17 +0800 Subject: [PATCH] =?UTF-8?q?=E4=BF=AE=E6=AD=A3=E4=BA=86=E6=96=87=E6=A1=A3?= =?UTF-8?q?=E4=B8=AD=E6=95=B0=E5=AD=A6=E5=85=AC=E5=BC=8F=E6=97=A0=E6=B3=95?= =?UTF-8?q?=E6=98=BE=E7=A4=BA=E7=9A=84=E9=97=AE=E9=A2=98?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- Day66-80/71.NumPy的应用-4.md | 23 ++--------------------- 1 file changed, 2 insertions(+), 21 deletions(-) diff --git a/Day66-80/71.NumPy的应用-4.md b/Day66-80/71.NumPy的应用-4.md index ac7d046..fbd784c 100644 --- a/Day66-80/71.NumPy的应用-4.md +++ b/Day66-80/71.NumPy的应用-4.md @@ -210,26 +210,7 @@ $$ 例如: $$ -\begin{bmatrix} -1 & 0 & 2 \\ --1 & 3 & 1 -\end{bmatrix} -\times -\begin{bmatrix} -3 & 1 \\ -2 & 1 \\ -1 & 0 -\end{bmatrix} -= -\begin{bmatrix} -(1 \times 3 + 0 \times 2 + 2 \times 1) & (1 \times 1 + 0 \times 1 + 2 \times 0) \\ -(-1 \times 3 + 3 \times 2 + 1 \times 1) & (-1 \times 1 + 3 \times 1 + 1 \times 0) -\end{bmatrix} -= -\begin{bmatrix} -5 & 1 \\ -4 & 2 -\end{bmatrix} +\begin{bmatrix} 1 & 0 & 2 \\\\ -1 & 3 & 1 \end{bmatrix} \times \begin{bmatrix} 3 & 1 \\\\ 2 & 1 \\\\ 1 & 0 \end{bmatrix} = \begin{bmatrix} (1 \times 3 + 0 \times 2 + 2 \times 1) & (1 \times 1 + 0 \times 1 + 2 \times 0) \\\\ (-1 \times 3 + 3 \times 2 + 1 \times 1) & (-1 \times 1 + 3 \times 1 + 1 \times 0) \end{bmatrix} = \begin{bmatrix} 5 & 1 \\\\ 4 & 2 \end{bmatrix} $$ 矩阵的乘法满足结合律和对矩阵加法的分配律: @@ -726,7 +707,7 @@ Polynomial.fit(x, y, deg=1).convert().coef array([-2.94883437e+02, 1.10333716e-01]) ``` -根据上面输出的结果,我们的回归方程应该是$\small{y=0.110333716x-294.883437}$。我们将这个回归方程绘制到刚才的散点图上,红色的点是我们的预测值,蓝色的点是历史数据,也就是真实值。 +根据上面输出的结果,我们的回归方程应该是 $\small{y=0.110333716x-294.883437}$ 。我们将这个回归方程绘制到刚才的散点图上,红色的点是我们的预测值,蓝色的点是历史数据,也就是真实值。 代码: