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Papers: 10.3390/e23091210

https://doi.org/10.3390/e23091210

Mood Disorder Detection in Adolescents by Classification Trees, Random Forests and XGBoost in Presence of Missing Data

Cited by: 4
Author(s): E Turska, Szymon Jurga, Jarosław Piskorski
Published: almost 4 years ago

Software Mentions 5

cran: mlr
Machine Learning in R
Papers that mentioned: 64
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: xgboost
Extreme Gradient Boosting
Papers that mentioned: 207
Very Likely Science (100)
pypi: mlr
Linear regression utility with inference tests, residual analysis, outlier visualization, multicollinearity test, and other features
Papers that mentioned: 64
Likely Science (40)
pypi: xgboost
XGBoost Python Package
Papers that mentioned: 207
Very Likely Science (90)