apunkt/ai-privacy-toolkit
1
0
Fork 0
mirror of https://github.com/IBM/ai-privacy-toolkit.git synced 2026-04-29 23:06:21 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

Prepare project for CI: cleanup dependencies, fix test data location, cleanup assert.

Browse source 
Signed-off-by: Maya Anderson <mayaa@il.ibm.com>
This commit is contained in:
Maya Anderson 2022-12-20 15:26:05 +02:00 • committed by abigailgold
parent 805a489201
commit 89bdcfc00e
3 changed files with 19 additions and 15 deletions
Download patch file Download diff file Expand all files Collapse all files

20
apt/utils/dataset_utils.py
View file

@ -54,7 +54,7 @@ def _load_diabetes(test_set_size: float = 0.3):
def get_german_credit_dataset_pd(test_set: float = 0.3):
"""
Loads the UCI German credit dataset from `tests/datasets/german` or downloads it from
Loads the UCI German credit dataset from `datasets/german` or downloads it from
https://archive.ics.uci.edu/ml/machine-learning-databases/statlog/german/ if necessary.
:param test_set: Proportion of the data to use as validation split (value between 0 and 1). Default is 0.3
@ -63,8 +63,8 @@ def get_german_credit_dataset_pd(test_set: float = 0.3):
"""
url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/statlog/german/german.data'
data_dir = '../datasets/german'
data_file = '../datasets/german/data'
data_dir = 'datasets/german'
data_file = 'datasets/german/data'
if not path.exists(data_dir):
mkdir(data_dir)
@ -133,7 +133,7 @@ def _modify_german_dataset(data):
def get_adult_dataset_pd():
"""
Loads the UCI Adult dataset from `tests/datasets/adult` or downloads it from
Loads the UCI Adult dataset from `datasets/adult` or downloads it from
https://archive.ics.uci.edu/ml/machine-learning-databases/adult/ if necessary.
:return: Dataset and labels as pandas dataframes. Returned as a tuple (x_train, y_train), (x_test, y_test)
@ -143,9 +143,9 @@ def get_adult_dataset_pd():
'label']
train_url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.data'
test_url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.test'
data_dir = '../datasets/adult'
train_file = '../datasets/adult/train'
test_file = '../datasets/adult/test'
data_dir = 'datasets/adult'
train_file = 'datasets/adult/train'
test_file = 'datasets/adult/test'
if not path.exists(data_dir):
mkdir(data_dir)
@ -235,7 +235,7 @@ def _modify_adult_dataset(data):
def get_nursery_dataset_pd(raw: bool = True, test_set: float = 0.2, transform_social: bool = False):
"""
Loads the UCI Nursery dataset from `tests/datasets/nursery` or downloads it from
Loads the UCI Nursery dataset from `datasets/nursery` or downloads it from
https://archive.ics.uci.edu/ml/machine-learning-databases/nursery/ if necessary.
:param raw: `True` if no preprocessing should be applied to the data. Otherwise, categorical data is one-hot
@ -251,8 +251,8 @@ def get_nursery_dataset_pd(raw: bool = True, test_set: float = 0.2, transform_so
:return: Dataset and labels as pandas dataframes. Returned as a tuple (x_train, y_train), (x_test, y_test)
"""
url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/nursery/nursery.data'
data_dir = '../datasets/nursery'
data_file = '../datasets/nursery/data'
data_dir = 'datasets/nursery'
data_file = 'datasets/nursery/data'
if not path.exists(data_dir):
mkdir(data_dir)