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authorChristoph Helma <helma@in-silico.ch>2016-04-21 14:29:23 +0200
committerChristoph Helma <helma@in-silico.ch>2016-04-21 14:29:23 +0200
commit4ebd80fee52c04bd36781f846eae60019918345d (patch)
treeab957e2025684365ddd4605ac4ad2f7ab100f6ec /lib/classification.rb
parent0b416e3b55a9256915a2427afe5bc112bcabc203 (diff)
initial classification probabilities
Diffstat (limited to 'lib/classification.rb')
-rw-r--r--lib/classification.rb38
1 files changed, 19 insertions, 19 deletions
diff --git a/lib/classification.rb b/lib/classification.rb
index 0202940..b9b66f0 100644
--- a/lib/classification.rb
+++ b/lib/classification.rb
@@ -5,28 +5,28 @@ module OpenTox
def self.weighted_majority_vote compound, params
neighbors = params[:neighbors]
- weighted_sum = {}
- sim_sum = 0.0
- confidence = 0.0
- neighbors.each do |row|
- sim = row["tanimoto"]
- row["features"][params[:prediction_feature_id].to_s].each do |act|
- weighted_sum[act] ||= 0
- weighted_sum[act] += sim
+ feature_id = params[:prediction_feature_id].to_s
+ sims = {}
+ neighbors.each do |n|
+ sim = n["tanimoto"]
+ n["features"][feature_id].each do |act|
+ sims[act] ||= []
+ sims[act] << sim
+ #sims[act] << 0.5*sim+0.5 # scale to 1-0.5
end
end
- case weighted_sum.size
- when 1
- return {:value => weighted_sum.keys.first, :confidence => weighted_sum.values.first/neighbors.size.abs}
- 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 {:value => prediction,:confidence => confidence}
- else
- bad_request_error "Cannot predict more than 2 classes, multinomial classifications is not yet implemented. Received classes were: '#{weighted.sum.keys}'"
+ sim_all = sims.collect{|a,s| s}.flatten
+ sim_sum = sim_all.sum
+ sim_max = sim_all.max
+ probabilities = {}
+ sims.each do |a,s|
+ probabilities[a] = s.sum/sim_sum
end
+ probabilities = probabilities.collect{|a,p| [a,sim_max*p]}.to_h
+ p_max = probabilities.collect{|a,p| p}.max
+ prediction = probabilities.key(p_max)
+ {:value => prediction,:probabilities => probabilities}
+
end
end
end