diff options
Diffstat (limited to 'report')
| -rw-r--r-- | report/plot_factory.rb | 90 | ||||
| -rwxr-xr-x | report/report_application.rb | 13 | ||||
| -rwxr-xr-x | report/report_content.rb | 12 | ||||
| -rwxr-xr-x | report/report_factory.rb | 62 | ||||
| -rwxr-xr-x | report/validation_data.rb | 21 |
5 files changed, 139 insertions, 59 deletions
diff --git a/report/plot_factory.rb b/report/plot_factory.rb index bf59960..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 @@ -294,15 +331,14 @@ module Reports private def self.transform_roc_predictions(validation_set, class_value, add_label=true ) if (validation_set.size > 1) - values = { :predicted_values => [], :actual_values => [], :confidence_values => []} + values = { :true_positives => [], :confidence_values => []} (0..validation_set.size-1).each do |i| - roc_values = validation_set.get(i).get_predictions.get_prediction_values(class_value) - values[:predicted_values] += roc_values[:predicted_values] + roc_values = validation_set.get(i).get_predictions.get_roc_prediction_values(class_value) + values[:true_positives ] += roc_values[:true_positives ] values[:confidence_values] += roc_values[:confidence_values] - values[:actual_values] += roc_values[:actual_values] end else - values = validation_set.validations[0].get_predictions.get_prediction_values(class_value) + values = validation_set.validations[0].get_predictions.get_roc_prediction_values(class_value) end tp_fp_rates = get_tp_fp_rates(values) labels = [] @@ -313,7 +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) @@ -321,7 +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] @@ -346,7 +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 @@ -357,8 +393,7 @@ module Reports # :predicted_values => [1, 0, 0, 1, 0, 1], # :actual_values => [0, 1, 0, 0, 1, 1]} roc_values = {:confidence_values => [0.9, 0.8, 0.7, 0.6, 0.5, 0.4], - :predicted_values => [1, 1, 1, 1, 1, 1], - :actual_values => [1, 0, 1, 0, 1, 0]} + :true_positives => [1, 1, 1, 0, 1, 0]} tp_fp_rates = get_tp_fp_rates(roc_values) labels = [] tp_fp_rates[:youden].each do |point,confidence| @@ -431,16 +466,15 @@ module Reports def self.get_tp_fp_rates(roc_values) c = roc_values[:confidence_values] - p = roc_values[:predicted_values] - a = roc_values[:actual_values] - raise "no prediction values for roc-plot" if p.size==0 + tp = roc_values[:true_positives] + raise "no prediction values for roc-plot" if tp.size==0 # hack for painting perfect/worst roc curve, otherwhise fp/tp-rate will always be 100% # determine if perfect/worst roc curve fp_found = false tp_found = false - (0..p.size-1).each do |i| - if a[i]!=p[i] + (0..tp.size-1).each do |i| + if tp[i]==0 fp_found |= true else tp_found |=true @@ -448,28 +482,26 @@ module Reports break if tp_found and fp_found end unless fp_found and tp_found #if perfect/worst add wrong/right instance with lowest confidence - a << (tp_found ? 0 : 1) - p << 1 + tp << (tp_found ? 0 : 1) c << -Float::MAX end - (0..p.size-2).each do |i| - ((i+1)..p.size-1).each do |j| + (0..tp.size-2).each do |i| + ((i+1)..tp.size-1).each do |j| if c[i]<c[j] c.swap!(i,j) - a.swap!(i,j) - p.swap!(i,j) + tp.swap!(i,j) end end end - #puts c.inspect+"\n"+a.inspect+"\n"+p.inspect+"\n\n" + #puts c.inspect+"\n"+tp.inspect+"\n\n" tp_rate = [0] fp_rate = [0] w = [1] c2 = [Float::MAX] - (0..p.size-1).each do |i| - if a[i]==p[i] + (0..tp.size-1).each do |i| + if tp[i]==1 tp_rate << tp_rate[-1]+1 fp_rate << fp_rate[-1] else diff --git a/report/report_application.rb b/report/report_application.rb index b96fb27..5fec6d1 100755 --- a/report/report_application.rb +++ b/report/report_application.rb @@ -50,6 +50,10 @@ get '/report/?' do end end +def wrap(s, width=78) + s.gsub(/(.{1,#{width}})(\s+|\Z)/, "\\1\n") +end + get '/report/:report_type' do perform do |rs| case request.env['HTTP_ACCEPT'].to_s @@ -60,8 +64,15 @@ get '/report/:report_type' do "Crossvalidations: "+url_for("/crossvalidation",:full) description = "A list of all "+params[:report_type]+" reports. To create a report, use the POST method." + if params[:report_type]=="algorithm_comparison" + description += "\n\nThis report can be used to compare the validation results of different algorithms that have been validated on the same dataset." + description += "\nThe following attributes can be compared with the t-test:" + description += "\n\n* All validation types:\n"+wrap((Validation::VAL_PROPS_SUM+Validation::VAL_PROPS_AVG).join(", "),120) + description += "\n* Classification validations:\n"+wrap(Validation::VAL_CLASS_PROPS.join(", "),120) + description += "\n* Regresssion validations:\n"+wrap(Validation::VAL_REGR_PROPS.join(", "),120) + end + post_params = [[:validation_uris]] - post_command = OpenTox::PostCommand.new request.url,"Create validation report" val_uri_description = params[:report_type]=="algorithm_comparison" ? "Separate multiple uris with ','" : nil # trick for easy report creation diff --git a/report/report_content.rb b/report/report_content.rb index 8c437a8..8d6d44b 100755 --- a/report/report_content.rb +++ b/report/report_content.rb @@ -179,13 +179,14 @@ class Reports::ReportContent def add_roc_plot( validation_set, accept_value, split_set_attribute=nil, - image_title = "ROC Plot", + image_title = nil, section_text="") #section_roc = @xml_report.add_section(@current_section, section_title) section_roc = @current_section prediction_set = validation_set.collect{ |v| v.get_predictions && v.get_predictions.confidence_values_available? } - + image_title = "ROC Plot (true class is '"+accept_value.to_s+"')" unless image_title + if prediction_set.size>0 if prediction_set.size!=validation_set.size section_text += "\nWARNING: roc plot information not available for all validation results" @@ -212,9 +213,10 @@ class Reports::ReportContent end def add_confidence_plot( validation_set, - accept_value = nil, + actual_accept_value = nil, + predicted_accept_value = nil, split_set_attribute = nil, - image_title = "Percent Correct vs Confidence Plot", + image_title = "Confidence Plot", section_text="") #section_conf = @xml_report.add_section(@current_section, section_title) @@ -232,7 +234,7 @@ class Reports::ReportContent begin plot_png = add_tmp_file("conf_plot", "png") plot_svg = add_tmp_file("conf_plot", "svg") - Reports::PlotFactory.create_confidence_plot( [plot_png[:path], plot_svg[:path]], prediction_set, accept_value, split_set_attribute, false ) + Reports::PlotFactory.create_confidence_plot( [plot_png[:path], plot_svg[:path]], prediction_set, actual_accept_value, predicted_accept_value, split_set_attribute, false ) @xml_report.add_imagefigure(section_conf, image_title, plot_png[:name], "PNG", 100, plot_svg[:name]) rescue Exception => ex msg = "WARNING could not create confidence plot: "+ex.message diff --git a/report/report_factory.rb b/report/report_factory.rb index 340f276..9995b42 100755 --- a/report/report_factory.rb +++ b/report/report_factory.rb @@ -5,19 +5,19 @@ VAL_ATTR_TRAIN_TEST = [ :model_uri, :training_dataset_uri, :test_dataset_uri, :p VAL_ATTR_CV = [ :algorithm_uri, :dataset_uri, :num_folds, :crossvalidation_fold ] # selected attributes of interest when performing classification -VAL_ATTR_CLASS = [ :num_instances, :num_unpredicted, :accuracy, :weighted_accuracy, :weighted_area_under_roc, - :area_under_roc, :f_measure, :true_positive_rate, :true_negative_rate ] +VAL_ATTR_CLASS = [ :num_instances, :num_unpredicted, :accuracy, :weighted_accuracy, :average_area_under_roc, + :area_under_roc, :f_measure, :true_positive_rate, :true_negative_rate, :positive_predictive_value, :negative_predictive_value ] VAL_ATTR_REGR = [ :num_instances, :num_unpredicted, :root_mean_squared_error, :weighted_root_mean_squared_error, :mean_absolute_error, :weighted_mean_absolute_error, :r_square, :weighted_r_square, :sample_correlation_coefficient ] -#VAL_ATTR_BAR_PLOT_CLASS = [ :accuracy, :weighted_area_under_roc, +#VAL_ATTR_BAR_PLOT_CLASS = [ :accuracy, :average_area_under_roc, # :area_under_roc, :f_measure, :true_positive_rate, :true_negative_rate ] -VAL_ATTR_BAR_PLOT_CLASS = [ :accuracy, :f_measure, :true_positive_rate, :true_negative_rate ] +VAL_ATTR_BAR_PLOT_CLASS = [ :accuracy, :f_measure, :true_positive_rate, :true_negative_rate, :positive_predictive_value, :negative_predictive_value ] VAL_ATTR_BAR_PLOT_REGR = [ :root_mean_squared_error, :mean_absolute_error, :r_square ] -VAL_ATTR_TTEST_REGR = [:r_square, :root_mean_squared_error] -VAL_ATTR_TTEST_CLASS = [:percent_correct, :weighted_area_under_roc] +VAL_ATTR_TTEST_REGR = [ :r_square, :root_mean_squared_error ] +VAL_ATTR_TTEST_CLASS = [ :accuracy, :average_area_under_roc ] # = Reports::ReportFactory @@ -76,11 +76,20 @@ module Reports::ReportFactory report.add_result(validation_set, [:validation_uri] + VAL_ATTR_TRAIN_TEST + VAL_ATTR_CLASS, "Results", "Results") report.add_confusion_matrix(val) report.add_section("Plots") - ([nil] + validation_set.get_accept_values).each do |accept_value| - report.add_roc_plot(validation_set, accept_value) - report.add_confidence_plot(validation_set, accept_value) - title = accept_value ? "Plots for predicted class-value '"+accept_value.to_s+"'" : "Plots for all predictions" - report.align_last_two_images title + if (validation_set.get_accept_values.size == 2) + if validation_set.get_true_accept_value!=nil + report.add_roc_plot(validation_set, validation_set.get_true_accept_value) + else + report.add_roc_plot(validation_set, validation_set.get_accept_values[0]) + report.add_roc_plot(validation_set, validation_set.get_accept_values[1]) + report.align_last_two_images "ROC Plots" + end + end + report.add_confidence_plot(validation_set) + validation_set.get_accept_values.each do |accept_value| + report.add_confidence_plot(validation_set, accept_value, nil) + report.add_confidence_plot(validation_set, nil, accept_value) + report.align_last_two_images "Confidence Plots" end report.end_section when "regression" @@ -127,12 +136,21 @@ module Reports::ReportFactory report.add_confusion_matrix(cv_set.validations[0]) report.add_section("Plots") [nil, :crossvalidation_fold].each do |split_attribute| - ([nil] + validation_set.get_accept_values).each do |accept_value| - report.add_roc_plot(validation_set, accept_value, split_attribute) - report.add_confidence_plot(validation_set, accept_value, split_attribute) - title = accept_value ? "Plots for predicted class-value '"+accept_value.to_s+"'" : "Plots for all predictions" - title += split_attribute ? ", separated by crossvalidation fold" : " (accumulated over all folds)" - report.align_last_two_images title + + if (validation_set.get_accept_values.size == 2) + if validation_set.get_true_accept_value!=nil + report.add_roc_plot(validation_set, validation_set.get_true_accept_value,split_attribute) + else + report.add_roc_plot(validation_set, validation_set.get_accept_values[0],split_attribute) + report.add_roc_plot(validation_set, validation_set.get_accept_values[1],split_attribute) + report.align_last_two_images "ROC Plots" + end + end + report.add_confidence_plot(validation_set,nil,nil,split_attribute) + validation_set.get_accept_values.each do |accept_value| + report.add_confidence_plot(validation_set, accept_value, nil,split_attribute) + report.add_confidence_plot(validation_set, nil, accept_value,split_attribute) + report.align_last_two_images "Confidence Plots" end end report.end_section @@ -199,8 +217,8 @@ module Reports::ReportFactory if (validation_set.num_different_values(:dataset_uri)>1) all_merged = validation_set.merge([:algorithm_uri, :dataset_uri, :crossvalidation_id, :crossvalidation_uri]) report.add_ranking_plots(all_merged, :algorithm_uri, :dataset_uri, - [:percent_correct, :weighted_area_under_roc, :true_positive_rate, :true_negative_rate] ) - report.add_result_overview(all_merged, :algorithm_uri, :dataset_uri, [:percent_correct, :weighted_area_under_roc, :true_positive_rate, :true_negative_rate]) + [:percent_correct, :average_area_under_roc, :true_positive_rate, :true_negative_rate] ) + report.add_result_overview(all_merged, :algorithm_uri, :dataset_uri, [:percent_correct, :average_area_under_roc, :true_positive_rate, :true_negative_rate]) end result_attributes = [:identifier,:crossvalidation_uri,:crossvalidation_report_uri]+VAL_ATTR_CV-[:crossvalidation_fold,:num_folds,:dataset_uri] @@ -222,6 +240,12 @@ module Reports::ReportFactory if params[:ttest_significance] ttest_significance = params[:ttest_significance].to_f end + + bar_plot_attributes += ttest_attributes + bar_plot_attributes.uniq! + + result_attributes += ttest_attributes + result_attributes.uniq! dataset_grouping.each do |validations| diff --git a/report/validation_data.rb b/report/validation_data.rb index aa146a6..f5ecae7 100755 --- a/report/validation_data.rb +++ b/report/validation_data.rb @@ -1,9 +1,9 @@ # the variance is computed when merging results for these attributes VAL_ATTR_VARIANCE = [ :area_under_roc, :percent_correct, :root_mean_squared_error, :mean_absolute_error, - :r_square, :accuracy, :weighted_area_under_roc, :weighted_accuracy, :weighted_root_mean_squared_error, :weighted_mean_absolute_error, + :r_square, :accuracy, :average_area_under_roc, :weighted_accuracy, :weighted_root_mean_squared_error, :weighted_mean_absolute_error, :weighted_r_square ] -VAL_ATTR_RANKING = [ :area_under_roc, :percent_correct, :true_positive_rate, :true_negative_rate, :weighted_area_under_roc, :accuracy, :f_measure ] +VAL_ATTR_RANKING = [ :area_under_roc, :percent_correct, :true_positive_rate, :true_negative_rate, :average_area_under_roc, :accuracy, :f_measure ] ATTR_NICE_NAME = {} @@ -263,6 +263,18 @@ module Reports return unique_value("get_accept_values") end + def get_true_accept_value() + accept_values = get_accept_values() + if accept_values.size==2 + if (accept_values[0] =~ TRUE_REGEXP and !(accept_values[1] =~ TRUE_REGEXP)) + return accept_values[0] + elsif (accept_values[1] =~ TRUE_REGEXP and !(accept_values[0] =~ TRUE_REGEXP)) + return accept_values[1] + end + end + nil + end + def get_accept_values_for_attr( attribute ) if !Validation::Validation.classification_property?(attribute) [] @@ -270,9 +282,8 @@ module Reports accept_values = get_accept_values() if !Validation::Validation.depends_on_class_value?(attribute) [ nil ] - elsif accept_values.size==2 and - Validation::Validation.complement_exists?(attribute) - [ accept_values[0] ] + elsif accept_values.size==2 and get_true_accept_value()!=nil and Validation::Validation.complement_exists?(attribute) + [ get_true_accept_value() ] else accept_values end |