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Updated scripts and workflows, as described in the manuscript
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LATEST RELEASE September 2017/CBDA_KO_Inference_ADNI_MN2_Dataset_complete.R
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LATEST RELEASE September 2017/CBDA_KO_Inference_Binomial_Dataset_complete.R
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LATEST RELEASE September 2017/CBDA_KO_Master_ADNI_MN2_Dataset_complete.R
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LATEST RELEASE September 2017/CBDA_KO_Master_ADNI_MN2_balanced_complete_INFERENCE.pipe
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LATEST RELEASE September 2017/CBDA_KO_Master_balanced_complete_INFERENCE.pipe
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load("~/Info_for_consolidation.RData") | ||
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for(j_global in 1:100) | ||
{ | ||
eval(parse(text=paste0("load(file= \"",workspace_directory,"CBDA_Inference_",j_global,"_",label,".RData\")"))) | ||
} | ||
eval(parse(text=paste0("save.image(\"",workspace_directory,"CBDA_Inference_",label,".RData\")"))) | ||
eval(parse(text=paste0("save.imag(\"",workspace_directory,"CBDA_Inference_",label,"_n",range_n,"_k",range_k,".RData\")"))) | ||
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#eval(parse(text=paste0("pdf(\"",workspace_directory,"Plot_Inference_",label,".pdf\")"))) | ||
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for(j_global in 1:100) | ||
{ | ||
eval(parse(text=paste0("qa_ALL$Features[",j_global,"] <- ",5+j_global,""))) | ||
eval(parse(text=paste0("qa_ALL$Inference_Acc[",j_global,"] <- Accuracy_",j_global,""))) | ||
eval(parse(text=paste0("qa_ALL$Inference_MSE[",j_global,"] <- MSE_",j_global,""))) | ||
} | ||
head(qa_ALL) | ||
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## Stopping Criteria for Accuracy and MSE Performance Metrics | ||
## Two more columns added with 0 (continue) and 1 (stop) | ||
for(i in 1:(100-1)) | ||
{ | ||
# F of Fisher test | ||
ifelse((qa_ALL$Inference_MSE[i]/qa_ALL$Features[i])/(qa_ALL$Inference_MSE[i+1]/qa_ALL$Features[i+1]) | ||
> qf(.95, df1=qa_ALL$Features[i], df2=qa_ALL$Features[i+1]), | ||
qa_ALL$StopMSE[i+1] <- 1, qa_ALL$StopMSE[i+1] <- 0) | ||
# Simple improvement (1%,5%, 0.05% in Accuracy) | ||
ifelse((qa_ALL$Inference_Acc[i+1]/qa_ALL$Inference_Acc[i])>1.0005, | ||
qa_ALL$StopAcc[i+1] <- 1, qa_ALL$StopAcc[i+1] <- 0) | ||
} | ||
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StopAcc <- which(qa_ALL$StopAcc == 1)[1] | ||
StopMSE <- which(qa_ALL$StopMSE == 1)[1] | ||
if(is.na(StopMSE)) | ||
{StopMSE <- StopAcc} | ||
print(StopAcc) | ||
print(StopMSE) | ||
# plot(1:length(qa_ALL$Inference_Acc),qa_ALL$Inference_Acc,xlab = "# top features", ylab = " Accuracy") | ||
# plot(1:length(qa_ALL$Inference_MSE),qa_ALL$Inference_MSE,xlab = "# top features", ylab = " MSE") | ||
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eval(parse(text=paste0("save.image(\"",workspace_directory,"CBDA_Inference_",label,".RData\")"))) | ||
eval(parse(text=paste0("save(qa_ALL,file= \"",workspace_directory,"CBDA_Inference_",label,"qa_ALL.RData\")"))) | ||
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#dev.off() |
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M misValperc Kcol_min Kcol_max Nrow_min Nrow_max | ||
9000 0 15 30 60 80 | ||
9000 0 5 15 30 60 | ||
9000 0 15 30 30 60 | ||
9000 0 5 15 60 80 | ||
9000 0 15 30 60 80 |