Add docs fro update_seq (#1735)

* Fix typos and messages in docs

* parameter.md: Add docs for updater_seq

Mention the updater_seq parameter which sets the order of the tree
updaters to run and also specifies which ones to run. This can be
useful when pruning is not required or even a custom plugin is
being built along with xgboost.

doc/jvm/java_intro.md

@@ -3,7 +3,9 @@ XGBoost4J Java API
 This tutorial introduces
 
 ## Data Interface
-Like the xgboost python module, xgboost4j use ```DMatrix``` to handle data, libsvm txt format file, sparse matrix in CSR/CSC format, and dense matrix is supported.
+Like the xgboost python module, xgboost4j uses ```DMatrix``` to handle data,
+libsvm txt format file, sparse matrix in CSR/CSC format, and dense matrix is
+supported.
 
 * To import ```DMatrix``` :
 ```java
@@ -97,7 +99,7 @@ import org.dmlc.xgboost4j.util.Trainer;
 ```java
 DMatrix trainMat = new DMatrix("train.svm.txt");
 DMatrix validMat = new DMatrix("valid.svm.txt");
-//specifiy a watchList to see the performance
+//specify a watchList to see the performance
 //any Iterable<Entry<String, DMatrix>> object could be used as watchList
 List<Entry<String, DMatrix>> watchs =  new ArrayList<>();
 watchs.add(new SimpleEntry<>("train", trainMat));

doc/parameter.md

@@ -73,6 +73,8 @@ Parameters for Tree Booster
   - range: (0, 1)
 * scale_pos_weight, [default=1]
   - Control the balance of positive and negative weights, useful for unbalanced classes. A typical value to consider: sum(negative  cases) / sum(positive cases) See [Parameters Tuning](how_to/param_tuning.md) for more discussion. Also see Higgs Kaggle competition demo for examples: [R](../demo/kaggle-higgs/higgs-train.R ), [py1](../demo/kaggle-higgs/higgs-numpy.py ), [py2](../demo/kaggle-higgs/higgs-cv.py ), [py3](../demo/guide-python/cross_validation.py)
+* updater_seq, [default="grow_colmaker,prune"]
+  - A comma separated string mentioning tThe sequence of Tree updaters that should be run. A tree updater is a pluggable operation performed on the tree at every step using the gradient information. Tree updaters can be registered using the plugin system provided.
 
 Additional parameters for Dart Booster
 --------------------------------------