def getUCIdata(name, N, dim, getOnline=False):
if getOnline:
link = "https://archive.ics.uci.edu/ml/machine-learning-databases/"
f = requests.get(link + name + "/" + name + ".data")
txt = f.text.splitlines()
else:
text_file = open(name + ".data", "r")
txt = text_file.readlines()
text_file.close()
x = numpy.zeros((N, dim))
labx = numpy.empty(N, dtype=object)
i = 0
for line in txt:
nr = line.split(',')
for j in range(dim):
try:
x[i, j] = float(nr[j])
except:
x[i, j] = numpy.nan
# finally get the label:
thislab = nr[dim].rstrip()
try:
labx[i] = float(thislab)
except:
labx[i] = thislab
i += 1
if (i >= N):
break
a = dataset.prdataset(x, labx)
return a
def read_mat(file):
"""
Reads a dataset from a .mat file and converts it into a prdataset
:param file: name of .mat file to be read from the /data folder
:return: a prdataset containing the features/labels read from the file
"""
import prtools # import prtools to get its installation path
data = loadmat(os.path.dirname(prtools.__file__) + '/data/' + file + '.mat')
if file == 'diabetes' or file == 'mfeat_zer' or file == 'mfeat_pix':
features = data['a'][0][0][0]
labels = data['a'][0][0][1]
else:
features = data['a']['data'][0][0]
labels = data['a']['nlab'][0][0]
a = dataset.prdataset(features, labels)
return a