We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
There was an error while loading. Please reload this page.
1 parent c540b30 commit 6d4914dCopy full SHA for 6d4914d
.gitignore
@@ -41,7 +41,7 @@ nips2010_pdf/
41
*.tgz
42
43
examples/cluster/joblib
44
-examples/applications/reuters/
+reuters/
45
benchmarks/bench_covertype_data/
46
47
*.prefs
examples/applications/plot_out_of_core_classification.py
@@ -194,8 +194,7 @@ def iterdocs(self):
194
195
# Create the data_streamer that parses Reuters SGML files and iterates on
196
# documents as a stream
197
-data_streamer = ReutersStreamReader(os.path.join(os.path.dirname(__file__),
198
- 'reuters')).iterdocs()
+data_streamer = ReutersStreamReader('reuters').iterdocs()
199
200
# Here we propose to learn a binary classification between the positive class
201
# and all other documents."""
0 commit comments