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Removed a warning
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prithagupta committed Mar 19, 2019
1 parent 8b1928f commit 55f9e96
Showing 1 changed file with 38 additions and 6 deletions.
44 changes: 38 additions & 6 deletions docs/notebooks/Rank-Net-Choice.ipynb
Expand Up @@ -146,7 +146,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 6,
"metadata": {},
"outputs": [
{
Expand Down Expand Up @@ -184,7 +184,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -194,9 +194,28 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 11,
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/pritha/.conda/envs/linenv/lib/python3.6/site-packages/sklearn/metrics/classification.py:1143: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in samples with no predicted labels.\n",
" 'precision', 'predicted', average, warn_for)\n"
]
},
{
"data": {
"text/plain": [
"0.5967395683047323"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from csrank.metrics_np import f1_measure\n",
"f1_measure(Y_test, y_pred)"
Expand All @@ -211,9 +230,22 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 9,
"metadata": {},
"outputs": [],
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(figsize=(5,5))\n",
"inst = np.random.choice(n_test)\n",
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