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Added logarithmic regression

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Not part of the course but fits better.
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scuti
2025-04-27 10:49:37 -07:00
parent b18a5cb42a
commit 67d1441303
1 changed files with 36 additions and 4 deletions
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stackoverflow-survey.ipynb
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@@ -268,6 +268,35 @@
" plt.legend(loc='lower center', bbox_to_anchor=(1.5,0)) \n",
" del y_pred, model, X, y\n",
"\n",
" def run_log_regression(self, color='pink', nodraw=True):\n",
" df = self.devs\n",
" X = df[self.key_x].to_frame().sort_values(by=self.key_x)\n",
" y = df[self.key_y].to_frame().sort_values(by=self.key_y)\n",
"\n",
" X_log = np.log(X)\n",
" x_fit = np.linspace(1, 40, len(y)).reshape(-1, 1)\n",
" \n",
" model = LinearRegression()\n",
" model.fit(X_log, y)\n",
" y_pred = model.predict(X_log)\n",
"\n",
" m = model.coef_[0][0]\n",
" b = model.intercept_[0]\n",
" print('+----------------------+')\n",
" print('%s log regression line for %s' % (color, self.language))\n",
" print('coefficient = %0.2f' % m)\n",
" print('intercept = %0.2f' % b)\n",
" rmse = root_mean_squared_error(y, y_pred)\n",
" print('rmse = %0.2f' % rmse)\n",
" r2 = r2_score(y, y_pred)\n",
" print('r2 score = %0.2f' % r2)\n",
" print('sample predictions:')\n",
" print(y_pred[3:6])\n",
" print('+----------------------+')\n",
" if nodraw:\n",
" return\n",
" plt.plot(X, y_pred, color=color, label=\"Log regression\")\n",
" plt.legend(loc='lower center', bbox_to_anchor=(1.5,0)) \n",
"\n",
" def export_image(self, base_filename = 'images/programmers-%s-%s.png'):\n",
" plt.figure(self.canvas)\n",
@@ -313,8 +342,9 @@
" x_shift=0, y_shift=-1.5e4, random=888,\n",
" color='cyan', name='Tuned regression line')\n",
"\n",
"python.run_regression(x_transform=log_base_a, change_base=1.20, risky=2, random=555, \n",
" color='pink', name='Risky regression line')\n",
"#python.run_regression(x_transform=log_base_a, change_base=1.20, risky=2, random=555, \n",
"# color='pink', name='Risky regression line')\n",
"python.run_log_regression(nodraw=False)\n",
"python.export_image()"
]
},
@@ -370,14 +400,16 @@
"c.run_regression()\n",
"c.run_regression(x_transform=log_base_a, change_base=1.3, \n",
" x_shift=2, y_shift=-5000, color='magenta', random=555)\n",
"c.run_regression(x_transform=log_base_a, change_base=1.3, risky=2, color='pink')\n",
"c.run_log_regression(nodraw=False)\n",
"c.export_image()"
]
},
{
"cell_type": "markdown",
"id": "b7026c56-3049-4e60-bbc6-ee548ff58297",
"metadata": {},
"metadata": {
"jp-MarkdownHeadingCollapsed": true
},
"source": [
"## Evaluation for C\n",
"\n",