Loading README.md +34 −10 Original line number Diff line number Diff line Loading @@ -219,6 +219,12 @@ Index splitting | |Multitask network |0.934 |0.830 | | |robust MT-NN |0.949 |0.827 | | |graph convolution |0.946 |0.860 | |hiv |logistic regression |0.864 |0.739 | | |Random Forest |0.999 |0.720 | | |IRV |0.841 |0.724 | | |Multitask network |0.761 |0.652 | | |robust MT-NN |0.780 |0.708 | | |graph convolution |0.876 |0.779 | Random splitting Loading Loading @@ -254,6 +260,12 @@ Random splitting | |Multitask network |0.951 |0.834 | | |robust MT-NN |0.959 |0.830 | | |graph convolution |0.975 |0.876 | |hiv |logistic regression |0.860 |0.806 | | |Random Forest |0.999 |0.850 | | |IRV |0.839 |0.809 | | |Multitask network |0.742 |0.715 | | |robust MT-NN |0.753 |0.727 | | |graph convolution |0.847 |0.803 | Scaffold splitting Loading Loading @@ -289,6 +301,12 @@ Scaffold splitting | |Multitask network |0.947 |0.862 | | |robust MT-NN |0.953 |0.890 | | |graph convolution |0.957 |0.823 | |hiv |logistic regression |0.858 |0.798 | | |Random Forest |0.946 |0.562 | | |IRV |0.847 |0.811 | | |Multitask network |0.775 |0.765 | | |robust MT-NN |0.785 |0.748 | | |graph convolution |0.867 |0.769 | * Regression Loading Loading @@ -327,20 +345,19 @@ Scaffold splitting |chembl |MT-NN regression |Index |0.443 |0.427 | | |MT-NN regression |Random |0.464 |0.434 | | |MT-NN regression |Scaffold |0.484 |0.361 | |qm7 |NN regression |Index |0.994 |0.969 | | |NN regression |Random |0.995 |0.992 | | |NN regression |Stratified |0.992 |0.992 | |qm7b |MT-NN regression |Index |0.883 |0.785 | | |MT-NN regression |Random |0.864 |0.838 | | |MT-NN regression |Stratified |0.871 |0.847 | |qm7 |NN regression |Index |0.997 |0.986 | | |NN regression |Random |0.999 |0.999 | | |NN regression |Stratified |0.999 |0.999 | |qm7b |MT-NN regression |Index |0.931 |0.803 | | |MT-NN regression |Random |0.923 |0.884 | | |MT-NN regression |Stratified |0.934 |0.884 | |kaggle |MT-NN regression |User-defined|0.748 |0.452 | |Dataset |Model |Splitting |Train score/MAE(kcal/mol)|Valid score/MAE(kcal/mol)| |----------------|-----------------|------------|-------------------------|-------------------------| |qm7 |NN regression |Index |22.1 |23.2 | | |NN regression |Random |16.2 |17.7 | | |NN regression |Stratified |20.5 |20.8 | | |NN regression |User-defined|9.0 |9.5 | |qm7 |NN regression |Index |11.0 |12.0 | | |NN regression |Random |7.12 |7.53 | | |NN regression |Stratified |6.61 |7.34 | * General features Loading @@ -355,6 +372,7 @@ Number of tasks and examples in the datasets |sider |27 |1427 | |toxcast |617 |8615 | |clintox |2 |1491 | |hiv |1 |41913 | |delaney |1 |1128 | |sampl |1 |643 | |kaggle |15 |173065 | Loading Loading @@ -402,6 +420,12 @@ Time needed for benchmark test(~20h in total) | |random forest |15 |200 | | |IRV |15 |10 | | |graph convolution |20 |130 | |hiv |logistic regression |180 |40 | | |Multitask network |180 |350 | | |robust MT-NN |180 |450 | | |random forest |180 |2800 | | |IRV |180 |200 | | |graph convolution |180 |1300 | |delaney |MT-NN regression |10 |40 | | |graphconv regression|10 |40 | | |random forest |10 |30 | Loading Loading
README.md +34 −10 Original line number Diff line number Diff line Loading @@ -219,6 +219,12 @@ Index splitting | |Multitask network |0.934 |0.830 | | |robust MT-NN |0.949 |0.827 | | |graph convolution |0.946 |0.860 | |hiv |logistic regression |0.864 |0.739 | | |Random Forest |0.999 |0.720 | | |IRV |0.841 |0.724 | | |Multitask network |0.761 |0.652 | | |robust MT-NN |0.780 |0.708 | | |graph convolution |0.876 |0.779 | Random splitting Loading Loading @@ -254,6 +260,12 @@ Random splitting | |Multitask network |0.951 |0.834 | | |robust MT-NN |0.959 |0.830 | | |graph convolution |0.975 |0.876 | |hiv |logistic regression |0.860 |0.806 | | |Random Forest |0.999 |0.850 | | |IRV |0.839 |0.809 | | |Multitask network |0.742 |0.715 | | |robust MT-NN |0.753 |0.727 | | |graph convolution |0.847 |0.803 | Scaffold splitting Loading Loading @@ -289,6 +301,12 @@ Scaffold splitting | |Multitask network |0.947 |0.862 | | |robust MT-NN |0.953 |0.890 | | |graph convolution |0.957 |0.823 | |hiv |logistic regression |0.858 |0.798 | | |Random Forest |0.946 |0.562 | | |IRV |0.847 |0.811 | | |Multitask network |0.775 |0.765 | | |robust MT-NN |0.785 |0.748 | | |graph convolution |0.867 |0.769 | * Regression Loading Loading @@ -327,20 +345,19 @@ Scaffold splitting |chembl |MT-NN regression |Index |0.443 |0.427 | | |MT-NN regression |Random |0.464 |0.434 | | |MT-NN regression |Scaffold |0.484 |0.361 | |qm7 |NN regression |Index |0.994 |0.969 | | |NN regression |Random |0.995 |0.992 | | |NN regression |Stratified |0.992 |0.992 | |qm7b |MT-NN regression |Index |0.883 |0.785 | | |MT-NN regression |Random |0.864 |0.838 | | |MT-NN regression |Stratified |0.871 |0.847 | |qm7 |NN regression |Index |0.997 |0.986 | | |NN regression |Random |0.999 |0.999 | | |NN regression |Stratified |0.999 |0.999 | |qm7b |MT-NN regression |Index |0.931 |0.803 | | |MT-NN regression |Random |0.923 |0.884 | | |MT-NN regression |Stratified |0.934 |0.884 | |kaggle |MT-NN regression |User-defined|0.748 |0.452 | |Dataset |Model |Splitting |Train score/MAE(kcal/mol)|Valid score/MAE(kcal/mol)| |----------------|-----------------|------------|-------------------------|-------------------------| |qm7 |NN regression |Index |22.1 |23.2 | | |NN regression |Random |16.2 |17.7 | | |NN regression |Stratified |20.5 |20.8 | | |NN regression |User-defined|9.0 |9.5 | |qm7 |NN regression |Index |11.0 |12.0 | | |NN regression |Random |7.12 |7.53 | | |NN regression |Stratified |6.61 |7.34 | * General features Loading @@ -355,6 +372,7 @@ Number of tasks and examples in the datasets |sider |27 |1427 | |toxcast |617 |8615 | |clintox |2 |1491 | |hiv |1 |41913 | |delaney |1 |1128 | |sampl |1 |643 | |kaggle |15 |173065 | Loading Loading @@ -402,6 +420,12 @@ Time needed for benchmark test(~20h in total) | |random forest |15 |200 | | |IRV |15 |10 | | |graph convolution |20 |130 | |hiv |logistic regression |180 |40 | | |Multitask network |180 |350 | | |robust MT-NN |180 |450 | | |random forest |180 |2800 | | |IRV |180 |200 | | |graph convolution |180 |1300 | |delaney |MT-NN regression |10 |40 | | |graphconv regression|10 |40 | | |random forest |10 |30 | Loading
