Style examples

This commit is contained in:
Danielius
2015-11-22 16:44:44 +02:00
parent 9293375bda
commit 2155771683
3 changed files with 76 additions and 34 deletions

View File

@@ -2,15 +2,25 @@ require 'rubygems'
require 'decisiontree'
include DecisionTree
# ---Continuous-----------------------------------------------------------------------------------------
# ---Continuous---
# Read in the training data
training, attributes = [], nil
File.open('data/continuous-training.txt','r').each_line { |line|
data = line.strip.chomp('.').split(',')
training = []
File.open('data/continuous-training.txt', 'r').each_line do |line|
data = line.strip.chomp('.').split(',')
attributes ||= data
training.push(data.collect {|v| (v == 'healthy') || (v == 'colic') ? (v == 'healthy' ? 1 : 0) : v.to_f})
}
training_data = data.collect do |v|
case v
when 'healthy'
1
when 'colic'
0
else
v.to_f
end
end
training.push(training_data)
end
# Remove the attribute row from the training data
training.shift
@@ -19,15 +29,25 @@ training.shift
dec_tree = ID3Tree.new(attributes, training, 1, :continuous)
dec_tree.train
#---- Test the tree....
# ---Test the tree---
# Read in the test cases
# Note: omit the attribute line (first line), we know the labels from the training data
# Note: omit the attribute line (first line), we know the labels from the training data
test = []
File.open('data/continuous-test.txt','r').each_line { |line|
data = line.strip.chomp('.').split(',')
test.push(data.collect {|v| (v == 'healthy') || (v == 'colic') ? (v == 'healthy' ? 1 : 0) : v.to_f})
}
File.open('data/continuous-test.txt', 'r').each_line do |line|
data = line.strip.chomp('.').split(',')
test_data = data.collect do |v|
if v == 'healthy' || v == 'colic'
v == 'healthy' ? 1 : 0
else
v.to_f
end
end
test.push(test_data)
end
# Let the tree predict the output and compare it to the true specified value
test.each { |t| predict = dec_tree.predict(t); puts "Predict: #{predict} ... True: #{t.last}"}
test.each do |t|
predict = dec_tree.predict(t)
puts "Predict: #{predict} ... True: #{t.last}"
end

View File

@@ -1,15 +1,25 @@
require 'rubygems'
require 'decisiontree'
# ---Discrete-----------------------------------------------------------------------------------------
# ---Discrete---
# Read in the training data
training, attributes = [], nil
File.open('data/discrete-training.txt','r').each_line { |line|
training = []
File.open('data/discrete-training.txt', 'r').each_line do |line|
data = line.strip.split(',')
attributes ||= data
training.push(data.collect {|v| (v == 'will buy') || (v == "won't buy") ? (v == 'will buy' ? 1 : 0) : v})
}
training_data = data.collect do |v|
case v
when 'will buy'
1
when "won't buy"
0
else
v
end
end
training.push(training_data)
end
# Remove the attribute row from the training data
training.shift
@@ -18,17 +28,31 @@ training.shift
dec_tree = DecisionTree::ID3Tree.new(attributes, training, 1, :discrete)
dec_tree.train
#---- Test the tree....
# ---Test the tree---
# Read in the test cases
# Note: omit the attribute line (first line), we know the labels from the training data
# Note: omit the attribute line (first line), we know the labels from the training data
test = []
File.open('data/discrete-test.txt','r').each_line { |line| data = line.strip.split(',')
test.push(data.collect {|v| (v == 'will buy') || (v == "won't buy") ? (v == 'will buy' ? 1 : 0) : v})
}
File.open('data/discrete-test.txt', 'r').each_line do |line|
data = line.strip.split(',')
test_data = data.collect do |v|
case v
when 'will buy'
1
when "won't buy"
0
else
v
end
end
training.push(test_data)
end
# Let the tree predict the output and compare it to the true specified value
test.each { |t| predict = dec_tree.predict(t); puts "Predict: #{predict} ... True: #{t.last}"; }
test.each do |t|
predict = dec_tree.predict(t)
puts "Predict: #{predict} ... True: #{t.last}"
end
# Graph the tree, save to 'discrete.png'
dec_tree.graph("discrete")
dec_tree.graph('discrete')

View File

@@ -2,7 +2,7 @@
require 'rubygems'
require 'decisiontree'
attributes = ['Temperature']
training = [
[36.6, 'healthy'],
@@ -10,19 +10,17 @@ training = [
[38, 'sick'],
[36.7, 'healthy'],
[40, 'sick'],
[50, 'really sick'],
[50, 'really sick']
]
# Instantiate the tree, and train it based on the data (set default to '1')
dec_tree = DecisionTree::ID3Tree.new(attributes, training, 'sick', :continuous)
dec_tree.train
test = [37, 'sick']
decision = dec_tree.predict(test)
puts "Predicted: #{decision} ... True decision: #{test.last}";
puts "Predicted: #{decision} ... True decision: #{test.last}"
# Graph the tree, save to 'tree.png'
dec_tree.graph("tree")
dec_tree.graph('tree')