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module Kmeans | |
class Demo | |
# data list and clusters | |
attr_accessor :data, :k | |
def initialize(data, k, i = 10) | |
@data = data | |
@k = k | |
clusters = [] | |
(1..@k).each do |cluster| | |
index = (@data.length * rand).to_i | |
point = Kmeans::Point.new(@data[index].first, @data[index].last) | |
clusters << Kmeans::Cluster.new(point) | |
end | |
group_elements(clusters) | |
(1..i).each do |iteration| | |
clusters.each do |c| | |
puts c.centroid.to_a.inspect | |
puts c.centroid! | |
end | |
end | |
end | |
#group elements by minimal distance | |
def group_elements(clusters) | |
@data.each do |d| | |
distance = [] | |
clusters.each_with_index do |cluster, index| | |
distance[index] = GpsWaypoints.distance(cluster.centroid.to_a, d) | |
end | |
a, b = distance.each_with_index.min | |
clusters[b].points << Kmeans::Point.new(d.first, d.last) | |
end | |
return clusters | |
end | |
end | |
end |
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