diff --git a/..gemspec b/..gemspec
new file mode 100644
index 0000000..67e63f2
--- /dev/null
+++ b/..gemspec
@@ -0,0 +1,19 @@
+# -*- encoding: utf-8 -*-
+lib = File.expand_path('../lib', __FILE__)
+$LOAD_PATH.unshift(lib) unless $LOAD_PATH.include?(lib)
+require './version'
+
+Gem::Specification.new do |gem|
+  gem.name          = "."
+  gem.version       = .::VERSION
+  gem.authors       = ["Chris Nelson"]
+  gem.email         = ["chris@gaslightsoftware.com"]
+  gem.description   = %q{TODO: Write a gem description}
+  gem.summary       = %q{TODO: Write a gem summary}
+  gem.homepage      = ""
+
+  gem.files         = `git ls-files`.split($/)
+  gem.executables   = gem.files.grep(%r{^bin/}).map{ |f| File.basename(f) }
+  gem.test_files    = gem.files.grep(%r{^(test|spec|features)/})
+  gem.require_paths = ["lib"]
+end
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..d87d4be
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,17 @@
+*.gem
+*.rbc
+.bundle
+.config
+.yardoc
+Gemfile.lock
+InstalledFiles
+_yardoc
+coverage
+doc/
+lib/bundler/man
+pkg
+rdoc
+spec/reports
+test/tmp
+test/version_tmp
+tmp
diff --git a/Gemfile b/Gemfile
new file mode 100644
index 0000000..cc56bff
--- /dev/null
+++ b/Gemfile
@@ -0,0 +1,4 @@
+source 'https://rubygems.org'
+
+# Specify your gem's dependencies in ..gemspec
+gemspec
diff --git a/decisiontree.gemspec b/decisiontree.gemspec
index 168768a..6c38bf0 100644
--- a/decisiontree.gemspec
+++ b/decisiontree.gemspec
@@ -47,7 +47,10 @@ Gem::Specification.new do |s|
      "examples/simple.rb"
   ]
   s.add_runtime_dependency "graphr"
-  
+  s.add_development_dependency "rspec"
+  s.add_development_dependency "rspec-given"
+  s.add_development_dependency "pry"
+
   if s.respond_to? :specification_version then
     current_version = Gem::Specification::CURRENT_SPECIFICATION_VERSION
     s.specification_version = 3
diff --git a/lib/decisiontree/id3_tree.rb b/lib/decisiontree/id3_tree.rb
index 2656ac1..dc3558a 100755
--- a/lib/decisiontree/id3_tree.rb
+++ b/lib/decisiontree/id3_tree.rb
@@ -15,9 +15,9 @@ class Object
   end
 end
 
-class Array 
-  def classification; collect { |v| v.last }; end 
-    
+class Array
+  def classification; collect { |v| v.last }; end
+
   # calculate information entropy
   def entropy
     return 0 if empty?
@@ -51,28 +51,34 @@ module DecisionTree
 
       @tree = id3_train(data2, attributes, default)
     end
-    
-    def id3_train(data, attributes, default, used={})
-      # Choose a fitness algorithm   
-      case @type
-        when :discrete; fitness = proc{|a,b,c| id3_discrete(a,b,c)} 
+
+    def type(attribute)
+      @type.is_a?(Hash) ? @type[attribute.to_sym] : @type
+    end
+
+    def fitness_for(attribute)
+      case type(attribute)
+        when :discrete; fitness = proc{|a,b,c| id3_discrete(a,b,c)}
         when :continuous; fitness = proc{|a,b,c| id3_continuous(a,b,c)}
       end
-      
-      return default if data.empty?                                               
+    end
+
+    def id3_train(data, attributes, default, used={})
+      return default if data.empty?
 
       # return classification if all examples have the same classification
       return data.first.last if data.classification.uniq.size == 1
 
       # Choose best attribute (1. enumerate all attributes / 2. Pick best attribute)
-      performance = attributes.collect { |attribute| fitness.call(data, attributes, attribute) }
+      performance = attributes.collect { |attribute| fitness_for(attribute).call(data, attributes, attribute) }
       max = performance.max { |a,b| a[0] <=> b[0] }
       best = Node.new(attributes[performance.index(max)], max[1], max[0])
       best.threshold = nil if @type == :discrete
-      @used.has_key?(best.attribute) ? @used[best.attribute] += [best.threshold] : @used[best.attribute] = [best.threshold]  
+      @used.has_key?(best.attribute) ? @used[best.attribute] += [best.threshold] : @used[best.attribute] = [best.threshold]
       tree, l = {best => {}}, ['>=', '<']
-      
-      case @type
+
+      fitness = fitness_for(best.attribute)
+      case type(best.attribute)
         when :continuous
           data.partition { |d| d[attributes.index(best.attribute)] >= best.threshold }.each_with_index  { |examples, i|
             tree[best][String.new(l[i])] = id3_train(examples, attributes, (data.classification.mode rescue 0), &fitness)
@@ -82,7 +88,7 @@ module DecisionTree
           partitions = values.collect { |val| data.select { |d| d[attributes.index(best.attribute)] == val } }
           partitions.each_with_index  { |examples, i|
             tree[best][values[i]] = id3_train(examples, attributes-[values[i]], (data.classification.mode rescue 0), &fitness)
-          }  
+          }
         end
 
       tree
@@ -96,32 +102,32 @@ module DecisionTree
       thresholds.pop
       #thresholds -= used[attribute] if used.has_key? attribute
 
-      gain = thresholds.collect { |threshold|   
+      gain = thresholds.collect { |threshold|
         sp = data.partition { |d| d[attributes.index(attribute)] >= threshold }
         pos = (sp[0].size).to_f / data.size
         neg = (sp[1].size).to_f / data.size
-       
+
         [data.classification.entropy - pos*sp[0].classification.entropy - neg*sp[1].classification.entropy, threshold]
       }.max { |a,b| a[0] <=> b[0] }
 
       return [-1, -1] if gain.size == 0
       gain
     end
-    
+
     # ID3 for discrete label cases
     def id3_discrete(data, attributes, attribute)
       values = data.collect { |d| d[attributes.index(attribute)] }.uniq.sort
       partitions = values.collect { |val| data.select { |d| d[attributes.index(attribute)] == val } }
       remainder = partitions.collect {|p| (p.size.to_f / data.size) * p.classification.entropy}.inject(0) {|i,s| s+=i }
-      
+
       [data.classification.entropy - remainder, attributes.index(attribute)]
     end
 
     def predict(test)
-       return (@type == :discrete ? descend_discrete(@tree, test) : descend_continuous(@tree, test))
+      descend(@tree, test)
     end
 
-    def graph(filename) 
+    def graph(filename)
       dgp = DotGraphPrinter.new(build_tree)
       dgp.write_to_file("#{filename}.png", "png")
     end
@@ -151,22 +157,20 @@ module DecisionTree
     end
 
   private
-    def descend_continuous(tree, test)
+    def descend(tree, test)
       attr = tree.to_a.first
       return @default if !attr
-      return attr[1]['>='] if !attr[1]['>='].is_a?(Hash) and test[@attributes.index(attr.first.attribute)] >= attr.first.threshold
-      return attr[1]['<'] if !attr[1]['<'].is_a?(Hash) and test[@attributes.index(attr.first.attribute)] < attr.first.threshold
-      return descend_continuous(attr[1]['>='],test) if test[@attributes.index(attr.first.attribute)] >= attr.first.threshold
-      return descend_continuous(attr[1]['<'],test) if test[@attributes.index(attr.first.attribute)] < attr.first.threshold 
-    end 
-    
-    def descend_discrete(tree, test)
-      attr = tree.to_a.first
-      return @default if !attr
-      return attr[1][test[@attributes.index(attr[0].attribute)]] if !attr[1][test[@attributes.index(attr[0].attribute)]].is_a?(Hash)
-      return descend_discrete(attr[1][test[@attributes.index(attr[0].attribute)]],test)
+      if type(attr.first.attribute) == :continuous
+        return attr[1]['>='] if !attr[1]['>='].is_a?(Hash) and test[@attributes.index(attr.first.attribute)] >= attr.first.threshold
+        return attr[1]['<'] if !attr[1]['<'].is_a?(Hash) and test[@attributes.index(attr.first.attribute)] < attr.first.threshold
+        return descend(attr[1]['>='],test) if test[@attributes.index(attr.first.attribute)] >= attr.first.threshold
+        return descend(attr[1]['<'],test) if test[@attributes.index(attr.first.attribute)] < attr.first.threshold
+      else
+        return attr[1][test[@attributes.index(attr[0].attribute)]] if !attr[1][test[@attributes.index(attr[0].attribute)]].is_a?(Hash)
+        return descend(attr[1][test[@attributes.index(attr[0].attribute)]],test)
+      end
     end
-    
+
     def build_tree(tree = @tree)
       return [] unless tree.is_a?(Hash)
       return [["Always", @default]] if tree.empty?
@@ -282,7 +286,7 @@ module DecisionTree
 
     def predict(test)
       @rules.each do |r|
-        prediction = r.predict(test) 
+        prediction = r.predict(test)
         return prediction, r.accuracy unless prediction.nil?
       end
       return @default, 0.0
diff --git a/spec/id3_spec.rb b/spec/id3_spec.rb
new file mode 100644
index 0000000..03b2ffa
--- /dev/null
+++ b/spec/id3_spec.rb
@@ -0,0 +1,64 @@
+require 'spec_helper'
+
+describe describe DecisionTree::ID3Tree do
+
+  describe "discrete attributes" do
+    Given(:labels) { ["hungry", "color"] }
+    Given(:data) do
+      [
+        ["yes", "red", "angry"],
+        ["no", "blue", "not angry"],
+        ["yes", "blue", "not angry"],
+        ["no", "red", "not angry"]
+      ]
+    end
+    Given(:tree) { DecisionTree::ID3Tree.new(labels, data, "not angry", :discrete) }
+    When { tree.train }
+    Then { tree.predict(["yes", "red"]).should == "angry" }
+    Then { tree.predict(["no", "red"]).should == "not angry" }
+  end
+
+  describe "discrete attributes" do
+    Given(:labels) { ["hunger", "happiness"] }
+    Given(:data) do
+      [
+        [8, 7, "angry"],
+        [6, 7, "angry"],
+        [7, 9, "angry"],
+        [7, 1, "not angry"],
+        [2, 9, "not angry"],
+        [3, 2, "not angry"],
+        [2, 3, "not angry"],
+        [1, 4, "not angry"]
+      ]
+    end
+    Given(:tree) { DecisionTree::ID3Tree.new(labels, data, "not angry", :continuous) }
+    When { tree.train }
+    Then { tree.graph("continuous") }
+    Then { tree.predict([7, 7]).should == "angry" }
+    Then { tree.predict([2, 3]).should == "not angry" }
+  end
+
+  describe "a mixture" do
+    Given(:labels) { ["hunger", "color"] }
+    Given(:data) do
+      [
+        [8, "red", "angry"],
+        [6, "red", "angry"],
+        [7, "red", "angry"],
+        [7, "blue", "not angry"],
+        [2, "red", "not angry"],
+        [3, "blue", "not angry"],
+        [2, "blue", "not angry"],
+        [1, "red", "not angry"]
+      ]
+    end
+    Given(:tree) { DecisionTree::ID3Tree.new(labels, data, "not angry", color: :discrete, hunger: :continuous) }
+    When { tree.train }
+    Then { tree.graph("continuous") }
+    Then { tree.predict([7, "red"]).should == "angry" }
+    Then { tree.predict([2, "blue"]).should == "not angry" }
+  end
+
+
+end
diff --git a/spec/spec_helper.rb b/spec/spec_helper.rb
new file mode 100644
index 0000000..7d706da
--- /dev/null
+++ b/spec/spec_helper.rb
@@ -0,0 +1,3 @@
+require 'rspec/given'
+require 'decisiontree'
+require 'pry'