From 8b42149a2541c2615221180b818d378a72701835 Mon Sep 17 00:00:00 2001 From: mhjensen Date: Fri, 4 Sep 2020 04:32:45 +0200 Subject: [PATCH] added bootstrap code --- doc/pub/How2ReadData/ipynb/How2ReadData.ipynb | 19 +++++++++++-------- 1 file changed, 11 insertions(+), 8 deletions(-) diff --git a/doc/pub/How2ReadData/ipynb/How2ReadData.ipynb b/doc/pub/How2ReadData/ipynb/How2ReadData.ipynb index 705d0f9c9..f184de74e 100644 --- a/doc/pub/How2ReadData/ipynb/How2ReadData.ipynb +++ b/doc/pub/How2ReadData/ipynb/How2ReadData.ipynb @@ -2013,17 +2013,19 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] }, - "metadata": {}, + "metadata": { + "needs_background": "light" + }, "output_type": "display_data" } ], @@ -2037,10 +2039,11 @@ "y = 2*x+0.01*np.random.randn(100,1)\n", "linreg = LinearRegression()\n", "linreg.fit(x,y)\n", - "xnew = np.array([[0],[1]])\n", - "ypredict = linreg.predict(xnew)\n", + "#ynew = linreg.predict(x)\n", + "#xnew = np.array([[0],[1]])\n", + "ypredict = linreg.predict(x)\n", "\n", - "plt.plot(xnew, ypredict, \"r-\")\n", + "plt.plot(x, ypredict, \"r-\")\n", "plt.plot(x, y ,'ro')\n", "plt.axis([0,1.0,0, 5.0])\n", "plt.xlabel(r'$x$')\n", @@ -3099,7 +3102,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.8" + "version": "3.8.3" } }, "nbformat": 4,