updates README

README.md

@@ -16,7 +16,7 @@ git clone the project, then run:
 
 ### Installing from Clojars
 
-    [org.clojars.bmabey/clj-ml "0.1.0"]
+    [org.clojars.bmabey/clj-ml "0.1.4"]
 
 ### Installing from Maven
 
@@ -25,7 +25,7 @@ git clone the project, then run:
     <dependency>
       <groupId>clj-ml</groupId>
       <artifactId>clj-ml</artifactId>
-      <version>0.1.0</version>
+      <version>0.1.4</version>
     </dependency>
 
 ## Supported algorithms
@@ -100,7 +100,7 @@ API documenation can be found [here](http://antoniogarrote.github.com/clj-ml/ind
 
 
     REPL>(def filtered-ds (filter-apply discretize ds))
-    
+
     REPL>; You can also use the filter's fn directly which will create and apply the filter:
     REPL>(def filtered-ds (unsupervised-discretize ds {:attributes [:sepallength :petallength]}))
     REPL>; The above way lends itself to the -> macro and is useful when using multiple filters.
@@ -108,7 +108,7 @@ API documenation can be found [here](http://antoniogarrote.github.com/clj-ml/ind
 
     REPL>; The eqivalent operation can be done with the ->> macro and make-apply-filter fn:
     REPL>(def filtered-ds (->> "file:///Applications/weka-3-6-2/data/iris.arff")
-                               (load-instances :arff) 
+                               (load-instances :arff)
                                (make-apply-filter :unsupervised-discretize {:attributes [0 2]}))
 
 ### Using classifiers