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model implementation » modular implementation (Expand Search), world implementation (Expand Search), time implementation (Expand Search)
code implementation » time implementation (Expand Search), world implementation (Expand Search), _ implementation (Expand Search)
code representing » model representing (Expand Search), models representing (Expand Search), tpd representing (Expand Search)
model implementation » modular implementation (Expand Search), world implementation (Expand Search), time implementation (Expand Search)
code implementation » time implementation (Expand Search), world implementation (Expand Search), _ implementation (Expand Search)
code representing » model representing (Expand Search), models representing (Expand Search), tpd representing (Expand Search)
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361
PepENS
Published 2025“…<br><br>Download and Use</p><p dir="ltr">The codes for Datasets 1 and 2 are found in the respective folders of this repository.…”
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362
Core data
Published 2025“…We divided the dataset into training and test sets, using 70% of the genes for training and 30% for testing. We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …”