Added readme.md with license.

Author: ptnplanet

README.md

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+Naive Bayes Classifier implemented in Java.
+==================
+
+Nothing special. It works and is well documented, so you should get it running without wasting too much time searching for other alternatives on the net.
+
+Here is an excerpt from the example. The classifier will classify strings as either positive or negative sentiment. Please refer to the full example for a more detailed documentation.
+
+```java
+Classifier<String, String> bayes = new BayesClassifier<String, String>();
+
+// Two examples to learn from.
+String[] positiveText = "I love sunny days".split("\\s");
+String[] negativeText = "I hate rain".split("\\s");
+
+// Learn by classifying examples. New categories can be added on the fly,
+// when they are first used.
+bayes.learn("positive", Arrays.asList(positiveText));
+bayes.learn("negative", Arrays.asList(negativeText));
+
+// Here are two unknown sentences to classify.
+String[] unknownText1 = "today is a sunny day".split("\\s");
+String[] unknownText2 = "there will be rain".split("\\s");
+
+System.out.println( // will output "positive"
+    bayes.classify(Arrays.asList(unknownText1)).getCategory());
+System.out.println( // will output "negative"
+    bayes.classify(Arrays.asList(unknownText2)).getCategory());
+
+// Get more detailed classification result.
+((BayesClassifier<String, String>) bayes).classifyDetailed(
+    Arrays.asList(unknownText1));
+
+// Change the memory capacity.
+bayes.setMemoryCapacity(500);
+```
+
+Forgetful learning
+------------------
+
+This classifier is forgetful. This means, that the classifier will forget recent classifications it uses for future classifications after - defaulting to 200 - classifications learned.
+This will ensure, that the classifier can react to ongoing changes in the user's habbits.
+
+Possible Performance issues
+------------------
+
+Performance improvements, I am currently thinking of:
+
+- Store the natural logarithms of the feature probabilities and add them together instead of multiplying the probability numbers
+
+The MIT License (MIT)
+------------------
+
+Copyright (c) 2012 Philipp Nolte
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+THE SOFTWARE.