README.md in lightgbm-0.1.1 vs README.md in lightgbm-0.1.2

@@ -14,10 +14,12 @@
 
 ```ruby
 gem 'lightgbm'
 ```
 
+## Getting Started
+
 Train a model
 
 ```ruby
 params = {objective: "regression"}
 train_set = LightGBM::Dataset.new(x_train, label: y_train)
@@ -28,17 +30,17 @@
 
 ```ruby
 booster.predict(x_test)
 ```
 
-Save the model
+Save the model to a file
 
 ```ruby
 booster.save_model("model.txt")
 ```
 
-Load a model from a file
+Load the model from a file
 
 ```ruby
 booster = LightGBM::Booster.new(model_file: "model.txt")
 ```
 
@@ -46,32 +48,34 @@
 
 ```ruby
 booster.feature_importance
 ```
 
-## Reference
+## Early Stopping
 
-### Booster
-
 ```ruby
-booster = LightGBM::Booster.new(model_str: "tree...")
-booster.to_json
-booster.model_to_string
-booster.current_iteration
+LightGBM.train(params, train_set, valid_set: [train_set, test_set], early_stopping_rounds: 5)
 ```
 
-### Dataset
+## CV
 
 ```ruby
-dataset = LightGBM::Dataset.new(data, label: label, weight: weight, params: params)
-dataset.num_data
-dataset.num_feature
-
-# note: only works with unquoted CSVs
-dataset = LightGBM::Dataset.new("data.csv", params: {headers: true, label: "name:label"})
-dataset.save_binary("train.bin")
-dataset.dump_text("train.txt")
+LightGBM.cv(params, train_set, nfold: 5, verbose_eval: true)
 ```
+
+## Reference
+
+This library follows the [Data Structure and Training APIs](https://lightgbm.readthedocs.io/en/latest/Python-API.html) for the Python library. A few differences are:
+
+- The default verbosity is `-1`
+- With the `cv` method, `stratified` is set to `false`
+
+Some methods and options are also missing at the moment. PRs welcome!
+
+## Helpful Resources
+
+- [Parameters](https://lightgbm.readthedocs.io/en/latest/Parameters.html)
+- [Parameter Tuning](https://lightgbm.readthedocs.io/en/latest/Parameters-Tuning.html)
 
 ## Credits
 
 Thanks to the [xgboost](https://github.com/PairOnAir/xgboost-ruby) gem for serving as an initial reference, and Selva Prabhakaran for the [test datasets](https://github.com/selva86/datasets).