improved README

Author: Hugo Hromic

README.md

@@ -60,7 +60,7 @@ recall = bcubed.recall(cdict, ldict)
 fscore = bcubed.fscore(precision, recall)
 ```
 
-You can see that also is included an **F-score** [2] (also called F-measure) function for your convenience. This function accepts non-standard values for the beta parameter if you need, as follows:
+You can see that also is included an **F-score** (also called F-measure) function for your convenience [2]. This function accepts non-standard values for the beta parameter if you need, as follows:
 
 ```python
 fscore = bcubed.fscore(precision, recall, beta=2.0)  # weights recall higher
@@ -72,4 +72,5 @@ A complete example can be found in the included ```example.py``` file, where the
 ## References
 
 [1] Amigó, Enrique, et al.: A comparison of Extrinsic Clustering Evaluation Metrics based on Formal Constraints. In: Information Retrieval 12.4 (2009): 461-486. ([download link](http://nlp.uned.es/docs/amigo2007a.pdf))
+
 [2] http://en.wikipedia.org/wiki/F1_score