def load_squares(n=1):
""" Squares dataset by Adrien PAVAO.
"""
if n==1:
data = apd.read_csv(os.path.join(CURRENT_PATH, 'squares1.csv'), header=None)
elif n==2:
data = apd.read_csv(os.path.join(CURRENT_PATH, 'squares2.csv'), header=None)
else:
raise Exception('n argument only accepts values 1 and 2')
return data
def load_boston():
""" Boston housing dataset.
https://www.cs.toronto.edu/~delve/data/boston/bostonDetail.html
"""
print('WARNING: target is missing for test set.')
train = apd.read_csv(os.path.join(CURRENT_PATH, 'boston_train.csv'))
test = apd.read_csv(os.path.join(CURRENT_PATH, 'boston_test.csv'))
data = apd.from_train_test(train, test)
data = data.imputation()
data.set_class('medv')
return data
def load_titanic():
""" Titanic dataset.
https://www.kaggle.com/c/titanic
"""
print('WARNING: target is missing for test set.')
train = apd.read_csv(os.path.join(CURRENT_PATH, 'titanic_train.csv'))
test = apd.read_csv(os.path.join(CURRENT_PATH, 'titanic_test.csv'))
data = apd.from_train_test(train, test)
data = data.encoding()
data = data.imputation()
data.set_class('Survived')
return data
def load_seeds():
""" Seeds dataset.
https://archive.ics.uci.edu/ml/datasets/seeds
"""
data = apd.read_csv(os.path.join(CURRENT_PATH, 'seeds.csv'))
data.set_class('V8')
return data
def load_diabetes():
""" Pima Indians Diabetes Dataset.
https://www.kaggle.com/uciml/pima-indians-diabetes-database
"""
data = apd.read_csv(os.path.join(CURRENT_PATH, 'diabetes.csv'), header=None)
data.set_class(8)
return data
def load_wine():
""" Wine quality dataset.
https://archive.ics.uci.edu/ml/datasets/Wine+Quality
"""
data = apd.read_csv(os.path.join(CURRENT_PATH, 'wine.csv'))
data.set_class('quality')
return data
def load_iris():
""" Iris dataset.
https://archive.ics.uci.edu/ml/datasets/Iris
"""
data = apd.read_csv(os.path.join(CURRENT_PATH, 'iris.csv'))
data = data.encoding()
data.set_class('Species')
return data
def load_mushrooms():
""" Mushrooms dataset.
https://archive.ics.uci.edu/ml/datasets/mushroom
"""
data = apd.read_csv(os.path.join(CURRENT_PATH, 'mushrooms.csv'))
data = data.encoding()
data.set_class('class')
return data
def load_adult():
""" Adult Income dataset.
https://archive.ics.uci.edu/ml/datasets/Adult
"""
data = apd.read_csv(os.path.join(CURRENT_PATH, 'adult.csv'))
data = data.encoding()
data.set_class('income')
return data
def load_boston():
""" Large Movie Review Dataset.
http://ai.stanford.edu/~amaas/data/sentiment/
"""
print('WARNING: NLP functionality is not available yet.')
data = apd.read_csv(os.path.join(CURRENT_PATH, 'imdb_dataset.csv'))
data = data.encoding()
data.set_class('sentiment')
return data