apunkt/ai-privacy-toolkit
1
0
Fork 0
mirror of https://github.com/IBM/ai-privacy-toolkit.git synced 2026-05-15 06:52:37 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

update notebooks

Browse source
This commit is contained in:
olasaadi 2022-03-23 21:52:06 +02:00
parent 06158c8508
commit 137167fb0c
3 changed files with 175 additions and 506 deletions
Download patch file Download diff file Expand all files Collapse all files

33
notebooks/membership_inference_dp_diabetes_reg.ipynb
View file

@ -29,7 +29,7 @@
},
{
"cell_type": "code",
"execution_count": 121,
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
@ -50,7 +50,7 @@
},
{
"cell_type": "code",
"execution_count": 122,
"execution_count": 2,
"metadata": {},
"outputs": [
{
@ -86,14 +86,14 @@
},
{
"cell_type": "code",
"execution_count": 123,
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.4954954954954955\n"
"0.527027027027027\n"
]
}
],
@ -131,7 +131,7 @@
},
{
"cell_type": "code",
"execution_count": 124,
"execution_count": 4,
"metadata": {},
"outputs": [
{
@ -141,6 +141,22 @@
"unique rows in original data: 221\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/olasaadi/PycharmProjects/ai-privacy-toolkit-internal/venv/lib/python3.8/site-packages/art/attacks/inference/membership_inference/black_box.py:262: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
" self.attack_model.fit(np.c_[x_1, x_2], y_ready) # type: ignore\n",
"/Users/olasaadi/PycharmProjects/ai-privacy-toolkit-internal/venv/lib/python3.8/site-packages/art/attacks/inference/membership_inference/black_box.py:262: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
" self.attack_model.fit(np.c_[x_1, x_2], y_ready) # type: ignore\n",
"/Users/olasaadi/PycharmProjects/ai-privacy-toolkit-internal/venv/lib/python3.8/site-packages/art/attacks/inference/membership_inference/black_box.py:262: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
" self.attack_model.fit(np.c_[x_1, x_2], y_ready) # type: ignore\n",
"/Users/olasaadi/PycharmProjects/ai-privacy-toolkit-internal/venv/lib/python3.8/site-packages/art/attacks/inference/membership_inference/black_box.py:262: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
" self.attack_model.fit(np.c_[x_1, x_2], y_ready) # type: ignore\n",
"/Users/olasaadi/PycharmProjects/ai-privacy-toolkit-internal/venv/lib/python3.8/site-packages/art/attacks/inference/membership_inference/black_box.py:262: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
" self.attack_model.fit(np.c_[x_1, x_2], y_ready) # type: ignore\n"
]
},
{
"name": "stdout",
"output_type": "stream",
@ -148,11 +164,12 @@
"k values: [5, 10, 20, 50, 75]\n",
"unique rows: [34, 19, 8, 4, 2]\n",
"model accuracy: [0.43165832354998956, 0.4509641063206041, -1.730181929385853, -5.577098823982753e+27, -1.2751609045828272e+25]\n",
"attack accuracy: [0.5, 0.47297297297297297, 0.49549549549549543, 0.5, 0.47297297297297297]\n"
"attack accuracy: [0.509009009009009, 0.481981981981982, 0.509009009009009, 0.5045045045045045, 0.4954954954954955]\n"
]
}
],
"source": [
"from apt.utils.datasets import ArrayDataset\n",
"from apt.anonymization import Anonymize\n",
"k_values=[5, 10, 20, 50, 75]\n",
"model_accuracy = []\n",
@ -165,7 +182,7 @@
"\n",
"for k in k_values:\n",
" anonymizer = Anonymize(k, QI, is_regression=True)\n",
" anon = anonymizer.anonymize(X_train, x_train_predictions)\n",
" anon = anonymizer.anonymize(ArrayDataset(X_train, x_train_predictions))\n",
" unique_values.append(len(np.unique(anon, axis=0)))\n",
" \n",
" anon_model = LinearRegression()\n",
@ -198,7 +215,7 @@
},
{
"cell_type": "code",
"execution_count": 124,
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": []