apunkt/ai-privacy-toolkit
1
0
Fork 0
mirror of https://github.com/IBM/ai-privacy-toolkit.git synced 2026-07-14 16:32:12 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

Reduce runtime of dataset assessment tests

Browse source 
Signed-off-by: abigailt <abigailt@il.ibm.com>
This commit is contained in:
abigailt 2023-05-31 14:54:16 +03:00
parent 7f0fef9ed5
commit 7d22423ac3
1 changed files with 3 additions and 3 deletions
Download patch file Download diff file Expand all files Collapse all files

6
tests/test_data_assessment.py
View file

@ -18,7 +18,7 @@ MIN_SHARE = 0.5
MIN_ROC_AUC = 0.0 MIN_ROC_AUC = 0.0
MIN_PRECISION = 0.0 MIN_PRECISION = 0.0
NUM_SYNTH_SAMPLES = 40000 NUM_SYNTH_SAMPLES = 400
NUM_SYNTH_COMPONENTS = 4 NUM_SYNTH_COMPONENTS = 4
iris_dataset_np = get_iris_dataset_np() iris_dataset_np = get_iris_dataset_np()
@ -109,8 +109,8 @@ def kde(n_samples, n_components, original_data):
digit_data = original_data digit_data = original_data
pca = PCA(n_components=n_components, whiten=False) pca = PCA(n_components=n_components, whiten=False)
data = pca.fit_transform(digit_data) data = pca.fit_transform(digit_data)
params = {'bandwidth': np.logspace(-1, 1, 20)} params = {'bandwidth': np.logspace(-1, 1, 10)}
grid = GridSearchCV(KernelDensity(), params, cv=5) grid = GridSearchCV(KernelDensity(), params, cv=2)
grid.fit(data) grid.fit(data)
kde_estimator = grid.best_estimator_ kde_estimator = grid.best_estimator_