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Hi - in your article, I believe that the comparisons of the ESOL, Lipo, and FreeSolv results to other models may be misleading. It appears based on Figure 6 that you may be using the normalized values of the regression results to calculate performance metrics. For example, the compound "CCCCC(C)O" in the raw data has a value of -0.89, whereas the value that you report in Figure 6 is 1.03, the same value that I get when I normalize the entire dataset using sklearns standard scaler. The same is also true of the other compounds in that figure. The majority/all of models in Table 4a use the unscaled values to calculate performance metrics, so comparing metrics calculated using the scaled vs. unscaled values would not be appropriate.
The text was updated successfully, but these errors were encountered:
Hi - in your article, I believe that the comparisons of the ESOL, Lipo, and FreeSolv results to other models may be misleading. It appears based on Figure 6 that you may be using the normalized values of the regression results to calculate performance metrics. For example, the compound "CCCCC(C)O" in the raw data has a value of -0.89, whereas the value that you report in Figure 6 is 1.03, the same value that I get when I normalize the entire dataset using sklearns standard scaler. The same is also true of the other compounds in that figure. The majority/all of models in Table 4a use the unscaled values to calculate performance metrics, so comparing metrics calculated using the scaled vs. unscaled values would not be appropriate.
The text was updated successfully, but these errors were encountered: