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Papers: 10.1017/S003329171800315X

https://doi.org/10.1017/S003329171800315X

A machine learning ensemble to predict treatment outcomes following an Internet intervention for depression

Cited by: 37
Author(s): Rahel Pearson, Derek Pisner, Björn Meyer, Jason Shumake, Christopher G. Beevers
Published: almost 8 years ago

Software Mentions 11

cran: dplyr
A Grammar of Data Manipulation
Papers that mentioned: 1,213
Very Likely Science (100)
cran: ggmap
Spatial Visualization with ggplot2
Papers that mentioned: 213
Very Likely Science (85)
cran: ggplot2
Create Elegant Data Visualisations Using the Grammar of Graphics
Papers that mentioned: 11,441
Very Likely Science (100)
cran: glmnet
Lasso and Elastic-Net Regularized Generalized Linear Models
Papers that mentioned: 1,607
Very Likely Science (100)
cran: gridExtra
Miscellaneous Functions for "Grid" Graphics
Papers that mentioned: 298
Very Likely Science (85)
cran: missForest
Nonparametric Missing Value Imputation using Random Forest
Papers that mentioned: 178
Very Likely Science (100)
cran: purrr
Functional Programming Tools
Papers that mentioned: 50
Very Likely Science (100)
cran: randomForest
Breiman and Cutler's Random Forests for Classification and Regression
Papers that mentioned: 1,447
Very Likely Science (100)
cran: tidyr
Tidy Messy Data
Papers that mentioned: 321
Very Likely Science (100)
cran: tidyverse
Easily Install and Load the 'Tidyverse'
Papers that mentioned: 1,023
Very Likely Science (100)
pypi: glmnet
Python wrapper for glmnet
Papers that mentioned: 1,607
Very Likely Science (100)