class ClassifierReborn::ContentNode
This is an internal data structure class for the LSI node. Save for #raw_vector_with, it should be fairly straightforward to understand. You should never have to use it directly.
Attributes
categories[RW]
lsi_norm[RW]
lsi_vector[RW]
raw_norm[RW]
raw_vector[RW]
word_hash[R]
Public Class Methods
new( word_hash, *categories )
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If text_proc is not specified, the source will be duck-typed via source.to_s
# File lib/classifier-reborn/lsi/content_node.rb, line 18 def initialize( word_hash, *categories ) @categories = categories || [] @word_hash = word_hash @lsi_norm, @lsi_vector = nil end
Public Instance Methods
raw_vector_with( word_list )
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Creates the raw vector out of #word_hash using word_list as the key for mapping the vector space.
# File lib/classifier-reborn/lsi/content_node.rb, line 41 def raw_vector_with( word_list ) if $GSL vec = GSL::Vector.alloc(word_list.size) else vec = Array.new(word_list.size, 0) end @word_hash.each_key do |word| vec[word_list[word]] = @word_hash[word] if word_list[word] end # Perform the scaling transform and force floating point arithmetic if $GSL sum = 0.0 vec.each {|v| sum += v } total_words = sum else total_words = vec.reduce(0, :+).to_f end total_unique_words = 0 if $GSL vec.each { |word| total_unique_words += 1 if word != 0.0 } else total_unique_words = vec.count{ |word| word != 0 } end # Perform first-order association transform if this vector has more # then one word in it. if total_words > 1.0 && total_unique_words > 1 weighted_total = 0.0 # Cache calculations, this takes too long on large indexes cached_calcs = Hash.new { |hash, term| hash[term] = (( term / total_words ) * Math.log( term / total_words )) } vec.each do |term| weighted_total += cached_calcs[term] if term > 0.0 end # Cache calculations, this takes too long on large indexes cached_calcs = Hash.new do |hash, val| hash[val] = Math.log( val + 1 ) / -weighted_total end vec.collect! { |val| cached_calcs[val] } end if $GSL @raw_norm = vec.normalize @raw_vector = vec else @raw_norm = Vector[*vec].normalize @raw_vector = Vector[*vec] end end
search_norm()
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Use this to fetch the appropriate search vector in normalized form.
# File lib/classifier-reborn/lsi/content_node.rb, line 35 def search_norm @lsi_norm || @raw_norm end
search_vector()
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Use this to fetch the appropriate search vector.
# File lib/classifier-reborn/lsi/content_node.rb, line 25 def search_vector @lsi_vector || @raw_vector end
transposed_search_vector()
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Method to access the transposed search vector
# File lib/classifier-reborn/lsi/content_node.rb, line 30 def transposed_search_vector search_vector.col end