@@ -19,32 +19,32 @@ internal class ConsolePrinter
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internal static void PrintMetrics ( int iteration , string trainerName , BinaryClassificationMetrics metrics , double bestMetric , double ? runtimeInSeconds , LogLevel logLevel , int iterationNumber = - 1 )
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{
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- logger . Log ( logLevel , CreateRow ( $ "{ iteration , - 4 } { trainerName , - 35 } { metrics ? . Accuracy ?? double . NaN , 9 : F4} { metrics ? . AreaUnderRocCurve ?? double . NaN , 8 : F4} { metrics ? . AreaUnderPrecisionRecallCurve ?? double . NaN , 8 : F4} { metrics ? . F1Score ?? double . NaN , 9 : F4} { runtimeInSeconds . Value , 9 : F1} { iterationNumber + 1 , 9 } ", Width ) ) ;
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+ logger . Log ( logLevel , CreateRow ( $ "{ iteration , - 4 } { trainerName , - 35 } { metrics ? . Accuracy ?? double . NaN , 9 : F4} { metrics ? . AreaUnderRocCurve ?? double . NaN , 8 : F4} { metrics ? . AreaUnderPrecisionRecallCurve ?? double . NaN , 8 : F4} { metrics ? . F1Score ?? double . NaN , 9 : F4} { runtimeInSeconds . Value , 9 : F1} { iterationNumber + 1 , 10 } ", Width ) ) ;
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}
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internal static void PrintMetrics ( int iteration , string trainerName , MulticlassClassificationMetrics metrics , double bestMetric , double ? runtimeInSeconds , LogLevel logLevel , int iterationNumber = - 1 )
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{
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- logger . Log ( logLevel , CreateRow ( $ "{ iteration , - 4 } { trainerName , - 35 } { metrics ? . MicroAccuracy ?? double . NaN , 14 : F4} { metrics ? . MacroAccuracy ?? double . NaN , 14 : F4} { runtimeInSeconds . Value , 9 : F1} { iterationNumber + 1 , 9 } ", Width ) ) ;
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+ logger . Log ( logLevel , CreateRow ( $ "{ iteration , - 4 } { trainerName , - 35 } { metrics ? . MicroAccuracy ?? double . NaN , 14 : F4} { metrics ? . MacroAccuracy ?? double . NaN , 14 : F4} { runtimeInSeconds . Value , 9 : F1} { iterationNumber + 1 , 10 } ", Width ) ) ;
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}
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internal static void PrintMetrics ( int iteration , string trainerName , RegressionMetrics metrics , double bestMetric , double ? runtimeInSeconds , LogLevel logLevel , int iterationNumber = - 1 )
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{
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- logger . Log ( logLevel , CreateRow ( $ "{ iteration , - 4 } { trainerName , - 35 } { metrics ? . RSquared ?? double . NaN , 9 : F4} { metrics ? . LossFunction ?? double . NaN , 12 : F2 } { metrics ? . MeanAbsoluteError ?? double . NaN , 15 : F2} { metrics ? . MeanSquaredError ?? double . NaN , 15 : F2} { metrics ? . RootMeanSquaredError ?? double . NaN , 12 : F2} { runtimeInSeconds . Value , 9 : F1} { iterationNumber + 1 , 9 } ", Width ) ) ;
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+ logger . Log ( logLevel , CreateRow ( $ "{ iteration , - 4 } { trainerName , - 35 } { metrics ? . RSquared ?? double . NaN , 8 : F4} { metrics ? . MeanAbsoluteError ?? double . NaN , 13 : F2} { metrics ? . MeanSquaredError ?? double . NaN , 12 : F2} { metrics ? . RootMeanSquaredError ?? double . NaN , 8 : F2} { runtimeInSeconds . Value , 9 : F1} { iterationNumber + 1 , 10 } ", Width ) ) ;
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}
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internal static void PrintBinaryClassificationMetricsHeader ( LogLevel logLevel )
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{
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- logger . Log ( logLevel , CreateRow ( $ "{ "" , - 4 } { "Trainer" , - 35 } { "Accuracy" , 9 } { "AUC" , 8 } { "AUPRC" , 8 } { "F1-score" , 9 } { "Duration" , 9 } { "#Iteration" , 9 } ", Width ) ) ;
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+ logger . Log ( logLevel , CreateRow ( $ "{ "" , - 4 } { "Trainer" , - 35 } { "Accuracy" , 9 } { "AUC" , 8 } { "AUPRC" , 8 } { "F1-score" , 9 } { "Duration" , 9 } { "#Iteration" , 10 } ", Width ) ) ;
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}
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internal static void PrintMulticlassClassificationMetricsHeader ( LogLevel logLevel )
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{
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- logger . Log ( logLevel , CreateRow ( $ "{ "" , - 4 } { "Trainer" , - 35 } { "MicroAccuracy" , 14 } { "MacroAccuracy" , 14 } { "Duration" , 9 } { "#Iteration" , 9 } ", Width ) ) ;
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+ logger . Log ( logLevel , CreateRow ( $ "{ "" , - 4 } { "Trainer" , - 35 } { "MicroAccuracy" , 14 } { "MacroAccuracy" , 14 } { "Duration" , 9 } { "#Iteration" , 10 } ", Width ) ) ;
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}
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internal static void PrintRegressionMetricsHeader ( LogLevel logLevel )
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{
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- logger . Log ( logLevel , CreateRow ( $ "{ "" , - 4 } { "Trainer" , - 35 } { "RSquared" , 8 } { "LossFn" , 10 } { " Absolute-loss", 13 } { "Squared-loss" , 12 } { "RMS-loss" , 10 } { "Duration" , 9 } { "#Iteration" , 9 } ", Width ) ) ;
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+ logger . Log ( logLevel , CreateRow ( $ "{ "" , - 4 } { "Trainer" , - 35 } { "RSquared" , 8 } { "Absolute-loss" , 13 } { "Squared-loss" , 12 } { "RMS-loss" , 8 } { "Duration" , 9 } { "#Iteration" , 10 } ", Width ) ) ;
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}
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internal static void ExperimentResultsHeader ( LogLevel logLevel , string mltask , string datasetName , string labelName , string time , int numModelsExplored )
@@ -58,7 +58,7 @@ internal static void ExperimentResultsHeader(LogLevel logLevel, string mltask, s
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logger . Log ( logLevel , CreateRow ( $ "{ "ML Task" , - 7 } : { mltask , - 20 } ", Width ) ) ;
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logger . Log ( logLevel , CreateRow ( $ "{ "Dataset" , - 7 } : { datasetName , - 25 } ", Width ) ) ;
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logger . Log ( logLevel , CreateRow ( $ "{ "Label" , - 6 } : { labelName , - 25 } ", Width ) ) ;
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- logger . Log ( logLevel , CreateRow ( $ "{ "Exploration time" , - 16 } : { time } Secs", Width ) ) ;
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+ logger . Log ( logLevel , CreateRow ( $ "{ "Total experiment time" , - 22 } : { time } Secs", Width ) ) ;
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logger . Log ( logLevel , CreateRow ( $ "{ "Total number of models explored" , - 30 } : { numModelsExplored } ", Width ) ) ;
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logger . Log ( logLevel , TABLESEPERATOR ) ;
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}
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