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Updated README

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1 parent b29c20d commit 74d2f5a0eb7cd356f0f2bf5957ea1b10d745f536 Didip Kerabat committed Nov 26, 2010
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15 README.markdown
@@ -4,7 +4,16 @@ Bayesian classifier on top of Redis
## Why on Redis?
-Because of its persistent but also in-memory data structures, Redis is perfect for weeks of machine learning.
+[Redis](http://code.google.com/p/redis) is a persistent in-memory database with supports for various data structures such as lists, sets, and ordered sets.
+All this data types can be manipulated with atomic operations to push/pop elements, add/remove elements, perform server side union, intersection, difference between sets, and so forth.
+
+Because of Redis properties:
+
+ * It is extremely easy to implement simple algorithm such as bayesian filter.
+
+ * The persistence of Redis means that the Bayesian implementation can be used in real production environment.
+
+ * Even though I don't particularly care about performance at the moment. Redis benchmarks give me confidence that the implementation can scale to relatively large training data.
## How to install?
@@ -22,6 +31,10 @@ Because of its persistent but also in-memory data structures, Redis is perfect f
# Then ask it to classify text.
bor.classify("awesome kick-ass ninja can still be lame.")
+## for Pythonistas
+
+BayesOnRedis is also available in Python. With the same API.
+
## Contributing
[Fork http://github.com/didip/bayes_on_redis](http://github.com/didip/bayes_on_redis) and send pull requests.

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