Updated documentation

README.md

@@ -31,26 +31,28 @@ JPMML-Evaluator is *de facto* the reference implementation of the PMML specifica
 * Calculation of auxiliary output fields according to the [Output](http://www.dmg.org/pmml/v4-3/Output.html) element:
   * Over 20 different result feature types.
 * Model verification according to the [ModelVerification](http://www.dmg.org/pmml/v4-3/ModelVerification.html) element.
+* Vendor extensions:
+  * Java-backed model, expression and predicate types - integrate any 3rd party Java library into PMML data flow.
+  * MathML prediction reports.
 
 For more information please see the [features.md](https://github.com/jpmml/jpmml-evaluator/blob/master/features.md) file.
 
 JPMML-Evaluator is interoperable with most popular statistics and data mining software:
 
 * [R](http://www.r-project.org/) and [Rattle](http://rattle.togaware.com/):
-  * [JPMML-R](https://github.com/jpmml/jpmml-r) library and [`r2pmml`](https://github.com/jpmml/r2pmml) package
-  * [`pmml`](https://cran.r-project.org/web/packages/pmml/) package
-  * [`pmmlTransformations`](https://cran.r-project.org/web/packages/pmmlTransformations/) package
+  * [JPMML-R](https://github.com/jpmml/jpmml-r) library and [`r2pmml`](https://github.com/jpmml/r2pmml) package.
+  * [`pmml`](https://cran.r-project.org/web/packages/pmml/) and [`pmmlTransformations`](https://cran.r-project.org/web/packages/pmmlTransformations/) packages.
 * [Python](http://www.python.org/) and [Scikit-Learn](http://scikit-learn.org/):
-  * [JPMML-SkLearn](https://github.com/jpmml/jpmml-sklearn) library and [`sklearn2pmml`](https://github.com/jpmml/sklearn2pmml) package
+  * [JPMML-SkLearn](https://github.com/jpmml/jpmml-sklearn) library and [`sklearn2pmml`](https://github.com/jpmml/sklearn2pmml) package.
 * [Apache Spark](http://spark.apache.org/):
-  * [JPMML-SparkML](https://github.com/jpmml/jpmml-sparkml) library
-  * [`mllib.pmml.PMMLExportable`](https://spark.apache.org/docs/latest/api/java/org/apache/spark/mllib/pmml/PMMLExportable.html) interface
+  * [JPMML-SparkML](https://github.com/jpmml/jpmml-sparkml) library.
+  * [`mllib.pmml.PMMLExportable`](https://spark.apache.org/docs/latest/api/java/org/apache/spark/mllib/pmml/PMMLExportable.html) interface.
 * [XGBoost](https://github.com/dmlc/xgboost):
-  * [JPMML-XGBoost](https://github.com/jpmml/jpmml-xgboost) library
+  * [JPMML-XGBoost](https://github.com/jpmml/jpmml-xgboost) library.
 * [LightGBM](https://github.com/Microsoft/LightGBM):
-  * [JPMML-LightGBM](https://github.com/jpmml/jpmml-lightgbm) library
+  * [JPMML-LightGBM](https://github.com/jpmml/jpmml-lightgbm) library.
 * [TensorFlow](http://tensorflow.org):
-  * [JPMML-TensorFlow](https://github.com/jpmml/jpmml-tensorflow) library
+  * [JPMML-TensorFlow](https://github.com/jpmml/jpmml-tensorflow) library.
 * [KNIME](http://www.knime.com/)
 * [RapidMiner](http://rapidminer.com/products/rapidminer-studio/)
 * [SAS](http://www.sas.com/en_us/software/analytics/enterprise-miner.html)
@@ -74,6 +76,11 @@ The current version is **1.3.10** (2 October, 2017).
 	<artifactId>pmml-evaluator</artifactId>
 	<version>1.3.10</version>
 </dependency>
+<dependency>
+	<groupId>org.jpmml</groupId>
+	<artifactId>pmml-evaluator-extension</artifactId>
+	<version>1.3.10</version>
+</dependency>
 ```
 
 # Usage #