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# cuts a classification dataset into balanced pieces
# let inact_act_ratio := majority_class.size/minority_class.size
# then: nr pieces = ceil(inact_act_ratio) if inact_act_ratio > 1.5
# each piece contains the complete minority class and ceil(inact_act_ratio) majority class compounds.
class Balancer
attr_accessor :inact_act_ratio, :act_hash, :inact_hash, :majority_splits, :nr_majority_splits, :errors, :datasets
# Supply a OpenTox::Dataset here
# Calculates inact_act_ratio, iff inact_act_ratio != +/-Infinity and no regression dataset is given
def initialize(dataset, feature_uri, creator_url)
@act_arr = []
@inact_arr = []
@inact_act_ratio = 1.0/0 # trick to define +infinity
@nr_majority_splits = 1 # +/-1 means: no split
@split = [] # splitted arrays with ids
@datasets = [] # result datasets
@errors = []
classification = true
if dataset.features.include?(feature_uri)
dataset.data.each do |i,a|
inchi = i
acts = a
acts.each do |act|
value = act[feature_uri]
if OpenTox::Utils.is_true?(value)
@act_arr << inchi
elsif OpenTox::Utils.classification?(value)
@inact_arr << inchi
else
classification = false
break;
end
end
end
@inact_act_ratio = @inact_arr.size.to_f / @act_arr.size.to_f unless (@act_arr.size == 0 or !classification) # leave alone for regression
set_nr_majority_splits
# perform majority split
@split = @nr_majority_splits > 0 ? shuffle_split(@inact_arr) : shuffle_split(@act_arr) unless @nr_majority_splits.abs == 1
@split.each do |s|
new_c = @nr_majority_splits > 0 ? s.concat(@act_arr) : s.concat(@inac_arr)
@datasets << dataset.create_new_dataset(new_c, [feature_uri], dataset.title, creator_url)
end
else
errors << "Feature not present in dataset."
end
errors << "Can not split regression dataset." unless classification
end
# sets nr of splits for majority class ('+', if inact_cnt > act_cnt, or '-' else), or leaves unchanged for illegal values.
def set_nr_majority_splits
@nr_majority_splits = @inact_act_ratio >= 1.5 ? @inact_act_ratio.ceil : ( @inact_act_ratio <= (2.0/3.0) ? -(1.0/@inact_act_ratio).ceil : ( @inact_act_ratio>1.0 ? 1 : -1) ) unless OpenTox::Utils.infinity?(@inact_act_ratio) # leave alone for regression
end
# does the actual shuffle and split
def shuffle_split (arr)
arr = arr.shuffle
arr.chunk(@nr_majority_splits.abs)
end
# turns a hash into a 2 col csv
def hsh2csv (hsh)
res=""
hsh.each do |k,v|
arr = [v,(@nr_majority_splits > 0 ? 0 : 1)]
res += arr.join(", ") + "\n"
end
res
end
end
class Array
# cuts an array into <num-pieces> chunks - returns a two-dimensional array
def chunk(pieces)
q, r = length.divmod(pieces)
(0..pieces).map { |i| i * q + [r, i].min }.enum_cons(2) \
.map { |a, b| slice(a...b) }
end
# shuffles the elements of an array
def shuffle( seed=nil )
srand seed.to_i if seed
sort_by { Kernel.rand }
end
# shuffels self
def shuffle!( seed=nil )
self.replace shuffle( seed )
end
end
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