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module OpenTox
class Validation
field :model_id, type: BSON::ObjectId
field :prediction_dataset_id, type: BSON::ObjectId
field :crossvalidation_id, type: BSON::ObjectId
field :test_dataset_id, type: BSON::ObjectId
field :nr_instances, type: Integer
field :nr_unpredicted, type: Integer
field :predictions, type: Hash
def prediction_dataset
Dataset.find prediction_dataset_id
end
def test_dataset
Dataset.find test_dataset_id
end
def model
Model::Lazar.find model_id
end
def self.create model, training_set, test_set, crossvalidation=nil
atts = model.attributes.dup # do not modify attributes of the original model
atts["_id"] = BSON::ObjectId.new
atts[:training_dataset_id] = training_set.id
validation_model = model.class.create model.prediction_feature, training_set, atts
validation_model.save
predictions = validation_model.predict test_set.substances
predictions.each{|cid,p| p.delete(:neighbors)}
nr_unpredicted = 0
predictions.each do |cid,prediction|
if prediction[:value]
tox = Substance.find(cid).toxicities[prediction[:prediction_feature_id].to_s]
#prediction[:measured] = Substance.find(cid).toxicities[prediction[:prediction_feature_id].to_s][test_set.id.to_s]
prediction[:measured] = tox[test_set.id.to_s] if tox
else
nr_unpredicted += 1
end
predictions.delete(cid) unless prediction[:value] and prediction[:measured]
end
validation = self.new(
:model_id => validation_model.id,
:test_dataset_id => test_set.id,
:nr_instances => test_set.substances.size,
:nr_unpredicted => nr_unpredicted,
:predictions => predictions#.sort{|a,b| p a; b[3] <=> a[3]} # sort according to confidence
)
validation.crossvalidation_id = crossvalidation.id if crossvalidation
validation.save
validation
end
end
class ClassificationValidation < Validation
end
class RegressionValidation < Validation
end
end
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