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Diffstat (limited to 'lib/caret.rb')
-rw-r--r-- | lib/caret.rb | 96 |
1 files changed, 96 insertions, 0 deletions
diff --git a/lib/caret.rb b/lib/caret.rb new file mode 100644 index 0000000..7e4f771 --- /dev/null +++ b/lib/caret.rb @@ -0,0 +1,96 @@ +module OpenTox + module Algorithm + + class Caret + # model list: https://topepo.github.io/caret/modelList.html + + def self.create_model_and_predict dependent_variables:, independent_variables:, weights:, method:, query_variables: + remove = [] + # remove independent_variables with single values + independent_variables.each_with_index { |values,i| remove << i if values.uniq.size == 1} + remove.sort.reverse.each do |i| + independent_variables.delete_at i + query_variables.delete_at i + end + if independent_variables.flatten.uniq == ["NA"] or independent_variables.flatten.uniq == [] + prediction = Algorithm::Regression::weighted_average dependent_variables:dependent_variables, weights:weights + prediction[:warning] = "No variables for regression model. Using weighted average of similar substances." + elsif + dependent_variables.size < 3 + prediction = Algorithm::Regression::weighted_average dependent_variables:dependent_variables, weights:weights + prediction[:warning] = "Insufficient number of neighbors (#{dependent_variables.size}) for regression model. Using weighted average of similar substances." + + else + dependent_variables.each_with_index do |v,i| + dependent_variables[i] = to_r(v) + end + independent_variables.each_with_index do |c,i| + c.each_with_index do |v,j| + independent_variables[i][j] = to_r(v) + end + end + query_variables.each_with_index do |v,i| + query_variables[i] = to_r(v) + end + begin + R.assign "weights", weights + r_data_frame = "data.frame(#{([dependent_variables]+independent_variables).collect{|r| "c(#{r.join(',')})"}.join(', ')})" + R.eval "data <- #{r_data_frame}" + R.assign "features", (0..independent_variables.size-1).to_a + R.eval "names(data) <- append(c('activities'),features)" # + R.eval "model <- train(activities ~ ., data = data, method = '#{method}', na.action = na.pass, allowParallel=TRUE)" + rescue => e + $logger.debug "R caret model creation error for:" + $logger.debug dependent_variables + $logger.debug independent_variables + prediction = Algorithm::Regression::weighted_average dependent_variables:dependent_variables, weights:weights + prediction[:warning] = "R caret model creation error. Using weighted average of similar substances." + return prediction + end + begin + R.eval "query <- data.frame(rbind(c(#{query_variables.join ','})))" + R.eval "names(query) <- features" + R.eval "prediction <- predict(model,query)" + value = R.eval("prediction").to_f + rmse = R.eval("getTrainPerf(model)$TrainRMSE").to_f + r_squared = R.eval("getTrainPerf(model)$TrainRsquared").to_f + prediction_interval = value-1.96*rmse, value+1.96*rmse + prediction = { + :value => value, + :rmse => rmse, + :r_squared => r_squared, + :prediction_interval => prediction_interval + } + rescue => e + $logger.debug "R caret prediction error for:" + $logger.debug self.inspect + prediction = Algorithm::Regression::weighted_average dependent_variables:dependent_variables, weights:weights + prediction[:warning] = "R caret prediction error. Using weighted average of similar substances" + return prediction + end + if prediction.nil? or prediction[:value].nil? + prediction = Algorithm::Regression::weighted_average dependent_variables:dependent_variables, weights:weights + prediction[:warning] = "Could not create local caret model. Using weighted average of similar substances." + end + end + prediction + + end + + # call caret methods dynamically, e.g. Caret.pls + def self.method_missing(sym, *args, &block) + args.first[:method] = sym.to_s + self.create_model_and_predict args.first + end + + def self.to_r v + return "F" if v == false + return "T" if v == true + return nil if v.is_a? Float and v.nan? + v + end + + end + end +end + |