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Make font sizes consistent across notebooks

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This commit is contained in:
Aurélien Geron
2021-11-27 23:03:26 +13:00
parent e72b210d97
commit 52d4f0a8c6
9 changed files with 141 additions and 156 deletions
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185
03_classification.ipynb
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@@ -86,7 +86,7 @@
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"plt.rc('font', size=12)\n",
"plt.rc('font', size=14)\n",
"plt.rc('axes', labelsize=14, titlesize=14)\n",
"plt.rc('legend', fontsize=14)\n",
"plt.rc('xtick',labelsize=10)\n",
@@ -689,7 +689,7 @@
"plt.ylabel('True Positive Rate (Recall)')\n",
"plt.grid()\n",
"plt.axis([0, 1, 0, 1])\n",
"plt.legend(loc=\"lower right\")\n",
"plt.legend(loc=\"lower right\", fontsize=13)\n",
"save_fig(\"roc_curve_plot\")\n",
"\n",
"plt.show()"
@@ -1033,6 +1033,7 @@
"from sklearn.metrics import ConfusionMatrixDisplay\n",
"\n",
"y_train_pred = cross_val_predict(sgd_clf, X_train_scaled, y_train, cv=3)\n",
"plt.rc('font', size=9) # not in the book – make the text smaller\n",
"ConfusionMatrixDisplay.from_predictions(y_train, y_train_pred)\n",
"plt.show()"
]
@@ -1043,6 +1044,7 @@
"metadata": {},
"outputs": [],
"source": [
"plt.rc('font', size=10) # not in the book\n",
"ConfusionMatrixDisplay.from_predictions(y_train, y_train_pred,\n",
" normalize=\"true\", values_format=\".0%\")\n",
"plt.show()"
@@ -1055,6 +1057,7 @@
"outputs": [],
"source": [
"sample_weight = (y_train_pred != y_train)\n",
"plt.rc('font', size=10) # not in the book\n",
"ConfusionMatrixDisplay.from_predictions(y_train, y_train_pred,\n",
" sample_weight=sample_weight,\n",
" normalize=\"true\", values_format=\".0%\")\n",
@@ -1076,8 +1079,10 @@
"source": [
"# not in the book – this code generates Figure 3–9\n",
"fig, axs = plt.subplots(nrows=1, ncols=2, figsize=(9, 4))\n",
"plt.rc('font', size=9)\n",
"ConfusionMatrixDisplay.from_predictions(y_train, y_train_pred, ax=axs[0])\n",
"axs[0].set_title(\"Confusion matrix\")\n",
"plt.rc('font', size=10)\n",
"ConfusionMatrixDisplay.from_predictions(y_train, y_train_pred, ax=axs[1],\n",
" normalize=\"true\", values_format=\".0%\")\n",
"axs[1].set_title(\"CM normalized by row\")\n",
@@ -1093,6 +1098,7 @@
"source": [
"# not in the book – this code generates Figure 3–10\n",
"fig, axs = plt.subplots(nrows=1, ncols=2, figsize=(9, 4))\n",
"plt.rc('font', size=10)\n",
"ConfusionMatrixDisplay.from_predictions(y_train, y_train_pred, ax=axs[0],\n",
" sample_weight=sample_weight,\n",
" normalize=\"true\", values_format=\".0%\")\n",
@@ -1102,7 +1108,8 @@
" normalize=\"pred\", values_format=\".0%\")\n",
"axs[1].set_title(\"Errors normalized by column\")\n",
"save_fig(\"confusion_matrix_plot_2\")\n",
"plt.show()"
"plt.show()\n",
"plt.rc('font', size=14) # make fonts great again"
]
},
{
@@ -1293,36 +1300,6 @@
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Extra Material — Calibrating Estimated Probabilities"
]
},
{
"cell_type": "code",
"execution_count": 89,
"metadata": {},
"outputs": [],
"source": [
"# TODO"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
@@ -1353,7 +1330,7 @@
},
{
"cell_type": "code",
"execution_count": 90,
"execution_count": 89,
"metadata": {},
"outputs": [],
"source": [
@@ -1379,7 +1356,7 @@
},
{
"cell_type": "code",
"execution_count": 91,
"execution_count": 90,
"metadata": {},
"outputs": [],
"source": [
@@ -1394,7 +1371,7 @@
},
{
"cell_type": "code",
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"execution_count": 91,
"metadata": {},
"outputs": [],
"source": [
@@ -1403,7 +1380,7 @@
},
{
"cell_type": "code",
"execution_count": 93,
"execution_count": 92,
"metadata": {},
"outputs": [],
"source": [
@@ -1419,7 +1396,7 @@
},
{
"cell_type": "code",
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"execution_count": 93,
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"source": [
@@ -1458,7 +1435,7 @@
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{
"cell_type": "code",
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"execution_count": 94,
"metadata": {},
"outputs": [],
"source": [
@@ -1467,7 +1444,7 @@
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{
"cell_type": "code",
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"outputs": [],
"source": [
@@ -1486,7 +1463,7 @@
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{
"cell_type": "code",
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"source": [
@@ -1519,7 +1496,7 @@
},
{
"cell_type": "code",
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"outputs": [],
"source": [
@@ -1544,7 +1521,7 @@
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{
"cell_type": "code",
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"outputs": [],
"source": [
@@ -1562,7 +1539,7 @@
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{
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@@ -1571,7 +1548,7 @@
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{
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"source": [
@@ -1587,7 +1564,7 @@
},
{
"cell_type": "code",
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"execution_count": 101,
"metadata": {},
"outputs": [],
"source": [
@@ -1603,7 +1580,7 @@
},
{
"cell_type": "code",
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"execution_count": 102,
"metadata": {
"tags": []
},
@@ -1643,7 +1620,7 @@
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{
"cell_type": "code",
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"source": [
@@ -1667,7 +1644,7 @@
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{
"cell_type": "code",
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@@ -1690,7 +1667,7 @@
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{
"cell_type": "code",
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@@ -1730,7 +1707,7 @@
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{
"cell_type": "code",
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"source": [
@@ -1747,7 +1724,7 @@
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{
"cell_type": "code",
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"metadata": {},
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"source": [
@@ -1756,7 +1733,7 @@
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{
"cell_type": "code",
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"metadata": {},
"outputs": [],
"source": [
@@ -1786,7 +1763,7 @@
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{
"cell_type": "code",
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"outputs": [],
"source": [
@@ -1811,7 +1788,7 @@
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{
"cell_type": "code",
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@@ -1827,7 +1804,7 @@
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{
"cell_type": "code",
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@@ -1836,7 +1813,7 @@
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{
"cell_type": "code",
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@@ -1845,7 +1822,7 @@
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{
"cell_type": "code",
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@@ -1868,7 +1845,7 @@
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{
"cell_type": "code",
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"cell_type": "code",
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@@ -1943,7 +1920,7 @@
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@@ -1960,7 +1937,7 @@
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@@ -1976,7 +1953,7 @@
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@@ -1993,7 +1970,7 @@
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"cell_type": "code",
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@@ -2010,7 +1987,7 @@
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@@ -2034,7 +2011,7 @@
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@@ -2061,7 +2038,7 @@
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@@ -2095,7 +2072,7 @@
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{
"cell_type": "code",
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@@ -2105,7 +2082,7 @@
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{
"cell_type": "code",
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@@ -2139,7 +2116,7 @@
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{
"cell_type": "code",
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@@ -2166,7 +2143,7 @@
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{
"cell_type": "code",
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@@ -2182,7 +2159,7 @@
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{
"cell_type": "code",
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@@ -2192,7 +2169,7 @@
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{
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@@ -2201,7 +2178,7 @@
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{
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@@ -2217,7 +2194,7 @@
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@@ -2231,7 +2208,7 @@
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@@ -2248,7 +2225,7 @@
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