README.md in xlearn-0.1.4 vs README.md in xlearn-0.1.5

@@ -6,11 +6,11 @@
 
 - Linear models
 - Factorization machines
 - Field-aware factorization machines
 
-[![Build Status](https://travis-ci.org/ankane/xlearn.svg?branch=master)](https://travis-ci.org/ankane/xlearn)
+[![Build Status](https://travis-ci.org/ankane/xlearn.svg?branch=master)](https://travis-ci.org/ankane/xlearn) [![Build status](https://ci.appveyor.com/api/projects/status/r7upg4073w7xct35/branch/master?svg=true)](https://ci.appveyor.com/project/ankane/xlearn/branch/master)
 
 ## Installation
 
 Add this line to your application’s Gemfile:
 
@@ -127,19 +127,25 @@
 
 ```ruby
 [[1, 2, 3], [4, 5, 6]]
 ```
 
-Or a Daru data frame
+Or a Numo array
 
 ```ruby
-Daru::DataFrame.from_csv("houses.csv")
+Numo::NArray.cast([[1, 2, 3], [4, 5, 6]])
 ```
 
-Or a Numo NArray
+Or a Rover data frame
 
 ```ruby
-Numo::DFloat.new(3, 2).seq
+Rover.read_csv("houses.csv")
+```
+
+Or a Daru data frame
+
+```ruby
+Daru::DataFrame.from_csv("houses.csv")
 ```
 
 ## Performance
 
 For large datasets, read data directly from files