diff options
Diffstat (limited to 'lib/classification.rb')
| -rw-r--r-- | lib/classification.rb | 28 |
1 files changed, 27 insertions, 1 deletions
diff --git a/lib/classification.rb b/lib/classification.rb index d71ab77..fc6fa77 100644 --- a/lib/classification.rb +++ b/lib/classification.rb @@ -3,10 +3,35 @@ module OpenTox class Classification + def self.weighted_majority_vote neighbors + return [nil,nil] if neighbors.empty? + weighted_sum = {} + sim_sum = 0.0 + neighbors.each do |row| + n,sim,acts = row + acts.each do |act| + weighted_sum[act] ||= 0 + weighted_sum[act] += sim + end + end + case weighted_sum.size + when 1 + return [weighted_sum.keys.first, 1.0] + when 2 + sim_sum = weighted_sum[weighted_sum.keys[0]] + sim_sum -= weighted_sum[weighted_sum.keys[1]] + sim_sum > 0 ? prediction = weighted_sum.keys[0] : prediction = weighted_sum.keys[1] + confidence = (sim_sum/neighbors.size).abs + return [prediction,confidence] + else + bad_request_error "Cannot predict more than 2 classes, multinomial classifications is not yet implemented. Received classes were: '#{weighted.sum.keys}'" + end + end + # Classification with majority vote from neighbors weighted by similarity # @param [Hash] params Keys `:activities, :sims, :value_map` are required # @return [Numeric] A prediction value. - def self.weighted_majority_vote(neighbors) + def self.fminer_weighted_majority_vote neighbors, training_dataset neighbor_contribution = 0.0 confidence_sum = 0.0 @@ -15,6 +40,7 @@ module OpenTox values = neighbors.collect{|n| n[2]}.uniq neighbors.each do |neighbor| + i = training_dataset.compound_ids.index n.id neighbor_weight = neighbor[1] activity = values.index(neighbor[2]) + 1 # map values to integers > 1 neighbor_contribution += activity * neighbor_weight |