All Notebooks | Help | Support | About
13th August 2019 @ 05:57

Next, a sweep of parameters on the ECFP was performed for both the LR and SVM method, considering the following: 

 

EC Depth = [4,5,6]

EC #Bits = [1024, 2048, 4096]

 

Again, 125 train/test splits were performed, and the distribution of MCC values were calculated. 

 

https://imgur.com/p5UAUFx

 

Here, the means of the MCC values for each model were calculated. 

 

Method_EC Depth_#Bits MeanMCCValue

svm_6_1024 0.594463

lr_6_1024 0.594463

svm_5_1024 0.642099
lr_5_1024 0.642099
svm_4_1024 0.648357
lr_4_1024 0.648357
lr_6_2048 0.653864
svm_6_2048 0.653864
lr_5_2048 0.658755
svm_5_2048 0.658755
svm_6_4096 0.658897
lr_6_4096 0.658897
svm_5_4096 0.667104
lr_5_4096 0.667104
svm_4_4096 0.667121
lr_4_4096 0.667121
lr_4_2048 0.673339
svm_4_2048 0.673339

 

The best methods were SVM and LR at depth 4, with 2048 bits. This gave an average MCC value of 0.67 +/- 0.1 for both.