Loading README.md +17 −18 Original line number Diff line number Diff line Loading @@ -283,7 +283,6 @@ Random splitting | |Robust MT-NN |0.822 |0.681 | | |Graph convolution |0.820 |0.717 | Scaffold splitting |Dataset |Model |Train score/ROC-AUC|Valid score/ROC-AUC| Loading @@ -300,12 +299,12 @@ Scaffold splitting | |NN classification |0.899 |0.961 | | |Robust NN |0.908 |0.956 | | |Graph convolution |0.968 |0.950 | |clintox |Logistic regression |0.960 |0.803 | |clintox |Logistic regression |0.965 |0.688 | | |Random forest |0.993 |0.735 | | |IRV |0.793 |0.718 | | |MT-NN classification|0.947 |0.862 | | |Robust MT-NN |0.953 |0.890 | | |Graph convolution |0.957 |0.823 | | |MT-NN classification|0.937 |0.828 | | |Robust MT-NN |0.956 |0.821 | | |Graph convolution |0.965 |0.900 | |hiv |Logistic regression |0.858 |0.798 | | |Random forest |0.946 |0.562 | | |IRV |0.847 |0.811 | Loading Loading @@ -388,7 +387,7 @@ Scaffold splitting | |Random forest |Scaffold |0.958 |0.329 | | |NN regression |Scaffold |0.831 |0.302 | | |Graphconv regression|Scaffold |0.882 |0.593 | |nci |MT-NN regression |Index |0.171 |0.062 | |nci |MT-NN regression |Index |0.690 |0.062 | | |Graphconv regression|Index |0.123 |0.048 | | |MT-NN regression |Random |0.168 |0.085 | | |Graphconv regression|Random |0.117 |0.076 | Loading Loading @@ -418,16 +417,16 @@ Scaffold splitting |qm8 |MT-NN regression |Index |0.783 |0.656 | | |MT-NN regression |Random |0.747 |0.660 | | |MT-NN regression |Stratified |0.756 |0.681 | |qm9 |MT-NN regression |Index |0.733 |0.791 | | |MT-NN regression |Random |0.811 |0.823 | | |MT-NN regression |Stratified |0.843 |0.818 | |qm9 |MT-NN regression |Index |0.733 |0.766 | | |MT-NN regression |Random |0.852 |0.833 | | |MT-NN regression |Stratified |0.764 |0.792 | |sampl |Random forest |Index |0.968 |0.736 | | |NN regression |Index |0.917 |0.749 | | |Graphconv regression|Index |0.982 |0.864 | | |NN regression |Index |0.917 |0.764 | | |Graphconv regression|Index |0.982 |0.903 | | |Random forest |Random |0.967 |0.752 | | |NN regression |Random |0.908 |0.711 | | |Graphconv regression|Random |0.987 |0.868 | | |Random forest |Scaffold |0.966 |0.473 | | |Random forest |Scaffold |0.966 |0.477 | | |NN regression |Scaffold |0.891 |0.217 | | |Graphconv regression|Scaffold |0.985 |0.666 | Loading Loading @@ -483,12 +482,12 @@ Time needed for benchmark test(~20h in total) | |Random forest |10 |80 | | |IRV |10 |10 | | |Graph convolution |15 |70 | |bbbp |Logistic regression | | | | |NN classification | | | | |Robust NN | | | | |Random forest | | | | |IRV | | | | |Graph convolution | | | |bbbp |Logistic regression |20 |10 | | |NN classification |20 |20 | | |Robust NN |20 |20 | | |Random forest |20 |120 | | |IRV |20 |10 | | |Graph convolution |20 |150 | |clintox |Logistic regression |15 |10 | | |MT-NN classification|15 |20 | | |Robust MT-NN |15 |30 | Loading deepchem/molnet/load_function/bace_datasets.py +1 −1 File changed.Contains only whitespace changes. Show changes Loading
README.md +17 −18 Original line number Diff line number Diff line Loading @@ -283,7 +283,6 @@ Random splitting | |Robust MT-NN |0.822 |0.681 | | |Graph convolution |0.820 |0.717 | Scaffold splitting |Dataset |Model |Train score/ROC-AUC|Valid score/ROC-AUC| Loading @@ -300,12 +299,12 @@ Scaffold splitting | |NN classification |0.899 |0.961 | | |Robust NN |0.908 |0.956 | | |Graph convolution |0.968 |0.950 | |clintox |Logistic regression |0.960 |0.803 | |clintox |Logistic regression |0.965 |0.688 | | |Random forest |0.993 |0.735 | | |IRV |0.793 |0.718 | | |MT-NN classification|0.947 |0.862 | | |Robust MT-NN |0.953 |0.890 | | |Graph convolution |0.957 |0.823 | | |MT-NN classification|0.937 |0.828 | | |Robust MT-NN |0.956 |0.821 | | |Graph convolution |0.965 |0.900 | |hiv |Logistic regression |0.858 |0.798 | | |Random forest |0.946 |0.562 | | |IRV |0.847 |0.811 | Loading Loading @@ -388,7 +387,7 @@ Scaffold splitting | |Random forest |Scaffold |0.958 |0.329 | | |NN regression |Scaffold |0.831 |0.302 | | |Graphconv regression|Scaffold |0.882 |0.593 | |nci |MT-NN regression |Index |0.171 |0.062 | |nci |MT-NN regression |Index |0.690 |0.062 | | |Graphconv regression|Index |0.123 |0.048 | | |MT-NN regression |Random |0.168 |0.085 | | |Graphconv regression|Random |0.117 |0.076 | Loading Loading @@ -418,16 +417,16 @@ Scaffold splitting |qm8 |MT-NN regression |Index |0.783 |0.656 | | |MT-NN regression |Random |0.747 |0.660 | | |MT-NN regression |Stratified |0.756 |0.681 | |qm9 |MT-NN regression |Index |0.733 |0.791 | | |MT-NN regression |Random |0.811 |0.823 | | |MT-NN regression |Stratified |0.843 |0.818 | |qm9 |MT-NN regression |Index |0.733 |0.766 | | |MT-NN regression |Random |0.852 |0.833 | | |MT-NN regression |Stratified |0.764 |0.792 | |sampl |Random forest |Index |0.968 |0.736 | | |NN regression |Index |0.917 |0.749 | | |Graphconv regression|Index |0.982 |0.864 | | |NN regression |Index |0.917 |0.764 | | |Graphconv regression|Index |0.982 |0.903 | | |Random forest |Random |0.967 |0.752 | | |NN regression |Random |0.908 |0.711 | | |Graphconv regression|Random |0.987 |0.868 | | |Random forest |Scaffold |0.966 |0.473 | | |Random forest |Scaffold |0.966 |0.477 | | |NN regression |Scaffold |0.891 |0.217 | | |Graphconv regression|Scaffold |0.985 |0.666 | Loading Loading @@ -483,12 +482,12 @@ Time needed for benchmark test(~20h in total) | |Random forest |10 |80 | | |IRV |10 |10 | | |Graph convolution |15 |70 | |bbbp |Logistic regression | | | | |NN classification | | | | |Robust NN | | | | |Random forest | | | | |IRV | | | | |Graph convolution | | | |bbbp |Logistic regression |20 |10 | | |NN classification |20 |20 | | |Robust NN |20 |20 | | |Random forest |20 |120 | | |IRV |20 |10 | | |Graph convolution |20 |150 | |clintox |Logistic regression |15 |10 | | |MT-NN classification|15 |20 | | |Robust MT-NN |15 |30 | Loading
deepchem/molnet/load_function/bace_datasets.py +1 −1 File changed.Contains only whitespace changes. Show changes
