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@ -2689,6 +2689,7 @@ def InitializeSecondStageCM (RemainingIds, setMaxLoopValue): |
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for column in pairDF: |
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listData = [] |
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randomZeroOne = random.randint(0, 1) |
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valuePerColumn = pairDF[column].iloc[randomZeroOne] |
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listData.append(valuePerColumn) |
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crossoverDF[column] = listData |
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@ -2709,7 +2710,6 @@ def InitializeSecondStageCM (RemainingIds, setMaxLoopValue): |
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localCrossMutr[1] = pd.concat([localCrossMutr[1], localCrossMutr[(loop+1)*4+1]], ignore_index=True) |
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localCrossMutr[2] = pd.concat([localCrossMutr[2], localCrossMutr[(loop+1)*4+2]], ignore_index=True) |
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localCrossMutr[3] = pd.concat([localCrossMutr[3], localCrossMutr[(loop+1)*4+3]], ignore_index=True) |
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allParametersPerfCrossMutrRFMC.append(localCrossMutr[0]) |
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allParametersPerfCrossMutrRFMC.append(localCrossMutr[1]) |
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allParametersPerfCrossMutrRFMC.append(localCrossMutr[2]) |
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@ -3050,7 +3050,7 @@ def InitializeSecondStageCM (RemainingIds, setMaxLoopValue): |
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allParametersPerformancePerModelEnsem[19] = pd.concat([allParametersPerformancePerModelEnsem[19], allParametersPerfCrossMutrGradBMC[3]], ignore_index=True) |
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allParametersPerformancePerModelEnsem[19] = pd.concat([allParametersPerformancePerModelEnsem[19], allParametersPerfCrossMutrGradBMM[3]], ignore_index=True) |
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allParametersPerfCrossMutr = allParametersPerfCrossMutrKNNCC + allParametersPerfCrossMutrKNNCM + allParametersPerfCrossMutrLRCC + allParametersPerfCrossMutrLRCM + allParametersPerfCrossMutrMLPCC + allParametersPerfCrossMutrMLPCM + allParametersPerfCrossMutrRFCC + allParametersPerfCrossMutrRFCM + allParametersPerfCrossMutrGradBCC + allParametersPerfCrossMutrGradBCM + allParametersPerfCrossMutrKNNMC + allParametersPerfCrossMutrKNNMM + allParametersPerfCrossMutrLRMC + allParametersPerfCrossMutrLRMM + allParametersPerfCrossMutrMLPMC + allParametersPerfCrossMutrMLPMM + allParametersPerfCrossMutrRFMC + allParametersPerfCrossMutrRFMM + allParametersPerfCrossMutrGradBMC + allParametersPerfCrossMutrGradBMM |
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allParametersPerfCrossMutr = allParametersPerfCrossMutrKNNCC + allParametersPerfCrossMutrKNNCM + allParametersPerfCrossMutrKNNMC + allParametersPerfCrossMutrKNNMM + allParametersPerfCrossMutrLRCC + allParametersPerfCrossMutrLRCM + allParametersPerfCrossMutrLRMC + allParametersPerfCrossMutrLRMM + allParametersPerfCrossMutrMLPCC + allParametersPerfCrossMutrMLPCM + allParametersPerfCrossMutrMLPMC + allParametersPerfCrossMutrMLPMM + allParametersPerfCrossMutrRFCC + allParametersPerfCrossMutrRFCM + allParametersPerfCrossMutrRFMC + allParametersPerfCrossMutrRFMM + allParametersPerfCrossMutrGradBCC + allParametersPerfCrossMutrGradBCM + allParametersPerfCrossMutrGradBMC + allParametersPerfCrossMutrGradBMM |
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allParametersPerformancePerModel[0] = allParametersPerformancePerModel[0] + allParametersPerfCrossMutrKNNCC[0] + allParametersPerfCrossMutrKNNCM[0] |
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allParametersPerformancePerModel[1] = pd.concat([allParametersPerformancePerModel[1], allParametersPerfCrossMutrKNNCC[1]], ignore_index=True) |
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