diff options
Diffstat (limited to 'report/plot_factory.rb')
| -rw-r--r-- | report/plot_factory.rb | 53 |
1 files changed, 45 insertions, 8 deletions
diff --git a/report/plot_factory.rb b/report/plot_factory.rb index 27e934d..2074ce5 100644 --- a/report/plot_factory.rb +++ b/report/plot_factory.rb @@ -130,8 +130,43 @@ module Reports end end + def self.confidence_plot_class_performance( validation_set, actual_accept_value, predicted_accept_value ) + true_class = nil + if actual_accept_value==nil and predicted_accept_value==nil + perf = "Accuracy" + elsif actual_accept_value!=nil + if validation_set.get_true_accept_value==actual_accept_value + perf = "True Positive Rate" + true_class = actual_accept_value + elsif validation_set.get_accept_values.size==2 and validation_set.get_true_accept_value==(validation_set.get_accept_values-[actual_accept_value])[0] + perf = "True Negative Rate" + true_class = validation_set.get_true_accept_value + else + perf = "True Positive Rate" + true_class = actual_accept_value + end + elsif predicted_accept_value!=nil + if validation_set.get_true_accept_value==predicted_accept_value + perf = "Positive Predictive Value" + true_class = predicted_accept_value + elsif validation_set.get_accept_values.size==2 and validation_set.get_true_accept_value==(validation_set.get_accept_values-[predicted_accept_value])[0] + perf = "Negative Predictive Value" + true_class = validation_set.get_true_accept_value + else + perf = "Positive Predictive Value" + true_class = predicted_accept_value + end + end + title = perf+" vs Confidence Plot" + title += " (with True-Class: '"+true_class.to_s+"')" if true_class!=nil + {:title =>title, :performance => perf} + end + - def self.create_confidence_plot( out_files, validation_set, class_value, split_set_attribute=nil, show_single_curves=false ) + def self.create_confidence_plot( out_files, validation_set, actual_accept_value = nil, + predicted_accept_value = nil, split_set_attribute=nil, show_single_curves=false ) + + raise "param combination not supported" if actual_accept_value!=nil and predicted_accept_value!=nil out_files = [out_files] unless out_files.is_a?(Array) LOGGER.debug "creating confidence plot for '"+validation_set.size.to_s+"' validations, out-file:"+out_files.inspect @@ -143,7 +178,7 @@ module Reports performance = [] attribute_values.each do |value| begin - data = transform_confidence_predictions(validation_set.filter({split_set_attribute => value}), class_value, false) + data = transform_confidence_predictions(validation_set.filter({split_set_attribute => value}), actual_accept_value, predicted_accept_value, false) names << split_set_attribute.to_s.nice_attr+" "+value.to_s confidence << data[:confidence][0] performance << data[:performance][0] @@ -155,17 +190,19 @@ module Reports out_files.each do |out_file| case validation_set.unique_feature_type when "classification" - RubyPlot::accuracy_confidence_plot(out_file, "Percent Correct vs Confidence Plot", "Confidence", "Percent Correct", names, confidence, performance) + info = confidence_plot_class_performance( validation_set, actual_accept_value, predicted_accept_value ) + RubyPlot::accuracy_confidence_plot(out_file, info[:title], "Confidence", info[:performance], names, confidence, performance) when "regression" RubyPlot::accuracy_confidence_plot(out_file, "RMSE vs Confidence Plot", "Confidence", "RMSE", names, confidence, performance, true) end end else - data = transform_confidence_predictions(validation_set, class_value, show_single_curves) + data = transform_confidence_predictions(validation_set, actual_accept_value, predicted_accept_value, show_single_curves) out_files.each do |out_file| case validation_set.unique_feature_type when "classification" - RubyPlot::accuracy_confidence_plot(out_file, "Percent Correct vs Confidence Plot", "Confidence", "Percent Correct", data[:names], data[:confidence], data[:performance]) + info = confidence_plot_class_performance( validation_set, actual_accept_value, predicted_accept_value ) + RubyPlot::accuracy_confidence_plot(out_file, info[:title], "Confidence", info[:performance], data[:names], data[:confidence], data[:performance]) when "regression" RubyPlot::accuracy_confidence_plot(out_file, "RMSE vs Confidence Plot", "Confidence", "RMSE", data[:names], data[:confidence], data[:performance], true) end @@ -312,7 +349,7 @@ module Reports end - def self.transform_confidence_predictions(validation_set, class_value, add_single_folds=false) + def self.transform_confidence_predictions(validation_set, actual_accept_value, predicted_accept_value, add_single_folds=false) if (validation_set.size > 1) @@ -320,7 +357,7 @@ module Reports sum_confidence_values = { :predicted_values => [], :actual_values => [], :confidence_values => []} (0..validation_set.size-1).each do |i| - confidence_values = validation_set.get(i).get_predictions.get_prediction_values(class_value) + confidence_values = validation_set.get(i).get_predictions.get_prediction_values(actual_accept_value, predicted_accept_value) sum_confidence_values[:predicted_values] += confidence_values[:predicted_values] sum_confidence_values[:confidence_values] += confidence_values[:confidence_values] sum_confidence_values[:actual_values] += confidence_values[:actual_values] @@ -345,7 +382,7 @@ module Reports return { :names => names, :performance => performance, :confidence => confidence, :faint => faint } else - confidence_values = validation_set.validations[0].get_predictions.get_prediction_values(class_value) + confidence_values = validation_set.validations[0].get_predictions.get_prediction_values(actual_accept_value, predicted_accept_value) pref_conf_rates = get_performance_confidence_rates(confidence_values, validation_set.unique_feature_type) return { :names => [""], :performance => [pref_conf_rates[:performance]], :confidence => [pref_conf_rates[:confidence]] } end |