diff --git a/Ordinal/preprocess_dataset_raw2tfidf.py b/Ordinal/preprocess_dataset_raw2tfidf.py
index 632546a..d472c3a 100644
--- a/Ordinal/preprocess_dataset_raw2tfidf.py
+++ b/Ordinal/preprocess_dataset_raw2tfidf.py
@@ -1,5 +1,5 @@
 import quapy as qp
-from Ordinal.utils import load_simple_sample_raw
+from Ordinal.utils import load_simple_sample_raw, load_samples_raw
 from quapy.data import LabelledCollection
 from sklearn.feature_extraction.text import TfidfVectorizer
 from os.path import join
@@ -19,6 +19,7 @@ datapath = './data'
 domain = 'Books'
 outname = domain + '-tfidf'
 
+
 def save_preprocessing_info(transformer):
     with open(join(datapath, outname, 'prep-info.txt'), 'wt') as foo:
         foo.write(f'{str(transformer)}\n')
@@ -30,11 +31,11 @@ os.makedirs(join(datapath, outname, 'app', 'dev_samples'), exist_ok=True)
 os.makedirs(join(datapath, outname, 'app', 'test_samples'), exist_ok=True)
 shutil.copyfile(join(datapath, domain, 'app', 'dev_prevalences.txt'), join(datapath, outname, 'app', 'dev_prevalences.txt'))
 shutil.copyfile(join(datapath, domain, 'app', 'test_prevalences.txt'), join(datapath, outname, 'app', 'test_prevalences.txt'))
-os.makedirs(join(datapath, outname, 'npp'), exist_ok=True)
-os.makedirs(join(datapath, outname, 'npp', 'dev_samples'), exist_ok=True)
-os.makedirs(join(datapath, outname, 'npp', 'test_samples'), exist_ok=True)
-shutil.copyfile(join(datapath, domain, 'npp', 'dev_prevalences.txt'), join(datapath, outname, 'npp', 'dev_prevalences.txt'))
-shutil.copyfile(join(datapath, domain, 'npp', 'test_prevalences.txt'), join(datapath, outname, 'npp', 'test_prevalences.txt'))
+os.makedirs(join(datapath, outname, 'real'), exist_ok=True)
+os.makedirs(join(datapath, outname, 'real', 'dev_samples'), exist_ok=True)
+os.makedirs(join(datapath, outname, 'real', 'test_samples'), exist_ok=True)
+shutil.copyfile(join(datapath, domain, 'real', 'dev_prevalences.txt'), join(datapath, outname, 'real', 'dev_prevalences.txt'))
+shutil.copyfile(join(datapath, domain, 'real', 'test_prevalences.txt'), join(datapath, outname, 'real', 'test_prevalences.txt'))
 
 
 tfidf = TfidfVectorizer(sublinear_tf=True, ngram_range=(1,2), min_df=5)
@@ -45,16 +46,17 @@ save_preprocessing_info(tfidf)
 pickle.dump(train, open(join(datapath, outname, 'training_data.pkl'), 'wb'), pickle.HIGHEST_PROTOCOL)
 
 
+
 def transform_folder_samples(protocol, splitname):
-    for i, sample in tqdm(enumerate(load_simple_sample_raw(join(datapath, domain, protocol, splitname), classes=train.classes_))):
+    for i, sample in tqdm(enumerate(load_samples_raw(join(datapath, domain, protocol, splitname), classes=train.classes_))):
         sample.instances = tfidf.transform(sample.instances)
         pickle.dump(sample, open(join(datapath, outname, protocol, splitname, f'{i}.pkl'), 'wb'), pickle.HIGHEST_PROTOCOL)
 
 
 transform_folder_samples('app', 'dev_samples')
 transform_folder_samples('app', 'test_samples')
-transform_folder_samples('npp', 'dev_samples')
-transform_folder_samples('npp', 'test_samples')
+transform_folder_samples('real', 'dev_samples')
+transform_folder_samples('real', 'test_samples')
 
 
 
diff --git a/Ordinal/utils.py b/Ordinal/utils.py
index fc74962..12f3887 100644
--- a/Ordinal/utils.py
+++ b/Ordinal/utils.py
@@ -48,8 +48,8 @@ def load_single_sample_pkl(parentdir, filename):
 #     return load_samples_folder(path_dir, filter, load_fn=load_simple_sample_npytxt)
 
 
-# def load_samples_raw(path_dir, filter=None, classes=None):
-#     return load_samples_folder(path_dir, filter, load_fn=load_simple_sample_raw, load_fn_kwargs={'classes': classes})
+def load_samples_raw(path_dir, filter=None, classes=None):
+    return load_samples_folder(path_dir, filter, load_fn=load_simple_sample_raw, classes=classes)
 
 
 # def load_samples_as_csv(path_dir, filter=None):