Class: Ai4r::Classifiers::Classifier

Inherits:
Object
  • Object
show all
Includes:
Data::Parameterizable
Defined in:
lib/ai4r/classifiers/classifier.rb

Overview

This class defines a common API for classifiers. All methods in this class must be implemented in subclasses.

Direct Known Subclasses

Hyperpipes, ID3, MultilayerPerceptron, NaiveBayes, OneR, Prism, ZeroR

Instance Method Summary collapse

Methods included from Data::Parameterizable

#get_parameters, included, #set_parameters

Instance Method Details

#build(data_set) ⇒ Object

Build a new classifier, using data examples found in data_set. The last attribute of each item is considered as the item class.

Raises:

  • (NotImplementedError) 


24
25
26
 
# File 'lib/ai4r/classifiers/classifier.rb', line 24

def build(data_set)
  raise NotImplementedError
end

#eval(data) ⇒ Object

You can evaluate new data, predicting its class. e.g.

classifier.eval(['New York',  '<30', 'F'])  # => 'Y'

Raises:

  • (NotImplementedError) 


31
32
33
 
# File 'lib/ai4r/classifiers/classifier.rb', line 31

def eval(data)
  raise NotImplementedError
end

#get_rules ⇒ Object

This method returns the generated rules in ruby code. e.g.

classifier.get_rules
  # =>  if age_range=='<30' then marketing_target='Y'
        elsif age_range=='[30-50)' and city=='Chicago' then marketing_target='Y'
        elsif age_range=='[30-50)' and city=='New York' then marketing_target='N'
        elsif age_range=='[50-80]' then marketing_target='N'
        elsif age_range=='>80' then marketing_target='Y'
        else raise 'There was not enough information during training to do a proper induction for this data element' end

It is a nice way to inspect induction results, and also to execute them:

age_range = '<30'
city='New York'
marketing_target = nil
eval classifier.get_rules   
puts marketing_target
  # =>  'Y'

Raises:

  • (NotImplementedError) 


53
54
55
 
# File 'lib/ai4r/classifiers/classifier.rb', line 53

def get_rules
  raise NotImplementedError
end