Class: ClusterTool

Inherits:
Object
  • Object
show all
Defined in:
lib/clustertool.rb

Overview

The main ClusterTool driver.

Class Method Summary collapse

Class Method Details

.cluster(database, table, columns, algorithm, args) ⇒ Object

Data is retrieved from the database and passed off to the appropriate algorithm.

Example: >> args = { >> :k => 3, >> :cycles => 10, >> } >> ClusterTool.cluster(“test.db”, “TestSimple2D”, [“Field1”, “Field2”], >> :kmeans, args)

> [[[0, 0], [-1, 0], [1, 0], [0, -1], [0, 1]], [[0, 10], [-1, 10], [1,

10], [0, 9], [0, 11]], [[-10, 0], [-11, 0], [-9, 0], [-10, -1], [-10, 1]]]

Example:

>> args = {

>> :epsilon = 1.5, >> :min_points = 2, >> } >> ClusterTool.cluster(“test.db”, “TestSimple1D”, [“Field”], :dbscan, >> args)

> 0], [-1, 0], [1, 0], [0, -1], [0, 1]], 1=>[[0, 10], [-1,

10], [1, 10], [0, 9], [0, 11]], 2=>[[-10, 0], [-11, 0], [-9, 0], [-10, -1], [-10, 1]]

Arguments: database: (String) table: (String) columns: [(String), …] algorithm: :kmeans or :dbscan args: { (Symbol) => (Numeric), … }



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# File 'lib/clustertool.rb', line 38

def self.cluster(database, table, columns, algorithm, args)
  db = SQLite3::Database.new(database)
  data = db.execute("select #{columns.join(", ")} from #{table};")

  case algorithm
  when :kmeans then return KMeans.cluster(data, args)
  when :dbscan then return DBSCAN.cluster(data, args)
  else raise ArgumentError, 'Unknown clustering algorithm' 
  end
end