Module: Functions_utils

Included in:
Weka::Classifier::Functions::GaussianProcesses, Weka::Classifier::Functions::LeastMedSq, Weka::Classifier::Functions::LibSVM, Weka::Classifier::Functions::LinearRegression, Weka::Classifier::Functions::PLSClassifier, Weka::Classifier::Functions::RBFNetwork, Weka::Classifier::Functions::SMO, Weka::Classifier::Functions::SMOreg, Weka::Classifier::Functions::SPegasos, Weka::Classifier::Functions::VotedPerceptron, Weka::Classifier::Functions::Winnow
Defined in:
lib/ruby-band/weka/classifiers/functions/functions_utils.rb

Overview

This module is used by the ‘functions’ classifiers from ‘functions.rb’ to inherit the following methods (instance and class methods)

Defined Under Namespace

Modules: ClassMethods

Class Method Summary collapse

Instance Method Summary collapse

Class Method Details

.included(base) ⇒ Object

Instance methods list



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# File 'lib/ruby-band/weka/classifiers/functions/functions_utils.rb', line 13

def self.included(base)
  base.extend(ClassMethods)
end

Instance Method Details

#cross_validate(fold) ⇒ Object

perform crossvalidation on a trained classifier ARGV: fold -> ‘int’ value



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# File 'lib/ruby-band/weka/classifiers/functions/functions_utils.rb', line 51

def cross_validate(fold)
  if self.class.data
    eval = Weka::Classifier::Evaluation.new self.class.data
    eval.crossValidateModel(self.class.ancestors[2].new, self.class.data, fold.to_java(:int), Random.new(1))
    eval.summary 
  else
    eval = Weka::Classifier::Evaluation.new @dataset
    eval.crossValidateModel(self.class.ancestors[1].new, @dataset, fold.to_java(:int), Random.new(1))
    eval.summary
  end
end

#description ⇒ Object

Return a description from the Weka Javadoc for the selected classifier



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# File 'lib/ruby-band/weka/classifiers/functions/functions_utils.rb', line 44

def description
  puts globalInfo
end

#init_function ⇒ Object 



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# File 'lib/ruby-band/weka/classifiers/functions/functions_utils.rb', line 6

def init_function
  set_options(self.class.options) if self.class.options 
  self.class.data.setClassIndex(self.class.class_index) if self.class.class_index
  buildClassifier(self.class.data)
end

#init_instance_classifier(&block) ⇒ Object 



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# File 'lib/ruby-band/weka/classifiers/functions/functions_utils.rb', line 17

def init_instance_classifier(&block)
  self.instance_eval(&block)
  @dataset.setClassIndex(@class_index)
  build_classifier(@dataset)
end

#list_options ⇒ Object

List available options



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# File 'lib/ruby-band/weka/classifiers/functions/functions_utils.rb', line 39

def list_options
  listOptions.map {|key| "#{key.synopsis} #{key.description}"}.join("\n")
end

#set_class_index(class_index) ⇒ Object

Set a class index for the input dataset



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# File 'lib/ruby-band/weka/classifiers/functions/functions_utils.rb', line 29

def set_class_index(class_index)
  @class_index = class_index 
end

#set_data(data) ⇒ Object

Set instance data for the instance classifier



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# File 'lib/ruby-band/weka/classifiers/functions/functions_utils.rb', line 24

def set_data(data)
  @dataset = data 
end

#set_options(options) ⇒ Object 



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# File 'lib/ruby-band/weka/classifiers/functions/functions_utils.rb', line 33

def set_options(options)
  options_inst = Utils.splitOptions(options)
  setOptions(options_inst)
end