- Timestamp:
- 09/19/13 17:25:13 (11 years ago)
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-
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trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Views/3.4/Exporters/SymbolicSolutionExcelExporter.cs
r9975 r9994 105 105 106 106 modelWorksheet.Cells[row, 1].Value = "Estimation Limits Lower"; 107 modelWorksheet.Cells[row, 2].Value = solution.Model.LowerEstimationLimit;107 modelWorksheet.Cells[row, 2].Value = Math.Max(solution.Model.LowerEstimationLimit, -9.99999999999999E+307); // minimal value supported by excel 108 108 modelWorksheet.Names.Add("EstimationLimitLower", modelWorksheet.Cells[row, 2]); 109 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000 ";109 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000E+00"; 110 110 row++; 111 111 112 112 modelWorksheet.Cells[row, 1].Value = "Estimation Limits Upper"; 113 modelWorksheet.Cells[row, 2].Value = solution.Model.UpperEstimationLimit;113 modelWorksheet.Cells[row, 2].Value = Math.Min(solution.Model.UpperEstimationLimit, 9.99999999999999E+307); // maximal value supported by excel 114 114 modelWorksheet.Names.Add("EstimationLimitUpper", modelWorksheet.Cells[row, 2]); 115 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000 ";115 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000E+00"; 116 116 row += 2; 117 117 … … 163 163 modelWorksheet.Cells[row, 2].Formula = string.Format("AVERAGE({0})", excelTrainingMSE); 164 164 modelWorksheet.Names.Add("TrainingMSE", modelWorksheet.Cells[row, 2]); 165 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000 ";165 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000E+00"; 166 166 row++; 167 167 … … 169 169 modelWorksheet.Cells[row, 2].Formula = string.Format("AVERAGE({0})", excelTestMSE); 170 170 modelWorksheet.Names.Add("TestMSE", modelWorksheet.Cells[row, 2]); 171 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000 ";171 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000E+00"; 172 172 row++; 173 173 174 174 modelWorksheet.Cells[row, 1].Value = "Mean absolute error (training)"; 175 175 modelWorksheet.Cells[row, 2].Formula = string.Format("AVERAGE({0})", excelTrainingAbsoluteError); 176 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000 ";176 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000E+00"; 177 177 row++; 178 178 179 179 modelWorksheet.Cells[row, 1].Value = "Mean absolute error (test)"; 180 180 modelWorksheet.Cells[row, 2].Formula = string.Format("AVERAGE({0})", excelTestAbsoluteError); 181 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000 ";181 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000E+00"; 182 182 row++; 183 183 184 184 modelWorksheet.Cells[row, 1].Value = "Mean error (training)"; 185 185 modelWorksheet.Cells[row, 2].Formula = string.Format("AVERAGE({0})", excelTrainingMeanError); 186 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000 ";186 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000E+00"; 187 187 row++; 188 188 189 189 modelWorksheet.Cells[row, 1].Value = "Mean error (test)"; 190 190 modelWorksheet.Cells[row, 2].Formula = string.Format("AVERAGE({0})", excelTestMeanError); 191 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000 ";191 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000E+00"; 192 192 row++; 193 193 … … 204 204 modelWorksheet.Cells[row, 1].Value = "Normalized Mean Squared error (training)"; 205 205 modelWorksheet.Cells[row, 2].Formula = string.Format("TrainingMSE / VAR({0})", excelTrainingTarget); 206 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000 ";206 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000E+00"; 207 207 row++; 208 208 209 209 modelWorksheet.Cells[row, 1].Value = "Normalized Mean Squared error (test)"; 210 210 modelWorksheet.Cells[row, 2].Formula = string.Format("TestMSE / VAR({0})", excelTestTarget); 211 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000 ";211 modelWorksheet.Cells[row, 2].Style.Numberformat.Format = "0.000E+00"; 212 212 213 213 modelWorksheet.Cells["A1:B" + row].AutoFitColumns();
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