Added Markdown to README.

README.md

@@ -0,0 +1,62 @@
+### Naive Bayesian Classification
+
+Perform naive Bayesian classification into an arbitrary number of classes on sets of strings.
+
+Copyright (c) 2011. Jake Brukhman. (jbrukh@gmail.com).
+All rights reserved.  See the LICENSE file for BSD-style
+license.
+
+------------
+
+#### Background
+
+See code comments for a refresher on naive Bayesian classifiers.
+
+------------
+
+#### Installation
+
+To install, simply:
+
+    $ make install
+
+To test, use:
+
+    $ make test
+
+------------
+
+#### Example
+
+To use the classifier, first you must create some classes
+and train it:
+
+    import . "bayesian"
+
+    const (
+        Good Class = "Good"
+        Bad Class = "Bad"
+    )
+
+    classifier := NewClassifier(Good, Bad)
+    goodStuff := []string{"tall", "rich", "handsome"}
+    badStuff  := []string{"poor", "smelly", "ugly"}
+    classifier.Learn(goodStuff, Good)
+    classifier.Learn(badStuff,  Bad)
+
+Then you can ascertain the scores of each class and
+the most likely class your data belongs to:
+
+    scores, likely, _ := classifier.Score(
+                            []string{"tall", "girl"}
+                         )
+
+Magnitude of the score indicates likelihood. Alternatively (but
+with some risk of float underflow), you can obtain actual probabilities:
+
+
+    probs, likely, _ := classifier.Probabilities(
+                            []string{"tall", "girl"}
+                         )
+
+Use wisely.