slightly changed doc

DanLiao · Nov 14, 2016 · bdaa6b1 · bdaa6b1
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Showing 4 changed files with 14 additions and 6 deletions.
diff --git a/README.md b/README.md
@@ -69,3 +69,10 @@ Acknowledgements:
 
 - [Pierre-François Gimenez](https://github.com/PFgimenez), for his valuable
   insights on software design.
+
+Contributing
+------------
+
+Any kind of feedback would be greatly appreciated (software design,
+documentation, improvement ideas, spelling, etc...). Please feel free to
+contirbute!
diff --git a/doc/source/getting_started.rst b/doc/source/getting_started.rst
@@ -75,11 +75,11 @@ Load a dataset with predefined folds
 .. literalinclude:: ../../examples/load_custom_dataset_predefined_folds.py
     :caption: From file ``examples/load_custom_dataset_predefined_folds.py``
     :name: load_custom_dataset_predefined_folds.py
-    :lines: 17-29
+    :lines: 18-30
 
 Of course, nothing prevents you from only loading a single file for training
 and a single file for testing. However, the ``folds_files`` parameter still
-needs to be a ``list`` (or any iterable).
+needs to be a ``list``.
 
 
 Advanced usage

diff --git a/examples/basic_usage.py b/examples/basic_usage.py
@@ -6,7 +6,7 @@
 from __future__ import (absolute_import, division, print_function,
                         unicode_literals)
 
-from recsys import NormalPredictor
+from recsys import SVD
 from recsys import Dataset
 from recsys import evaluate
 
@@ -16,8 +16,8 @@
 data = Dataset.load_builtin('ml-100k')
 data.split(n_folds=3)
 
-# This algorithm predicts a random rating sampled from a normal distribution.
-algo = NormalPredictor()
+# We'll use the famous SVD algorithm.
+algo = SVD()
 
 # Evaluate performances of our algorithm on the dataset.
 perf = evaluate(algo, data, measures=['RMSE', 'MAE'])

diff --git a/examples/load_custom_dataset_predefined_folds.py b/examples/load_custom_dataset_predefined_folds.py
@@ -8,14 +8,15 @@
 
 from __future__ import (absolute_import, division, print_function,
                         unicode_literals)
+import os
 
 from recsys import BaselineOnly
 from recsys import Dataset
 from recsys import evaluate
 from recsys import Reader
 
 # path to dataset folder
-files_dir = '/home/nico/.recsys_data/ml-100k/ml-100k/'  # change this
+files_dir = os.path.exapanduser('~/.recsys_data/ml-100k/ml-100k/')
 
 # This time, we'll use the built-in reader.
 reader = Reader('ml-100k')