Prediction: Difference between revisions

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** [https://topepo.github.io/caret/variable-importance.html 15 Variable Importance] from '''caret'''
** [https://topepo.github.io/caret/variable-importance.html 15 Variable Importance] from '''caret'''
** [https://www.linkedin.com/pulse/how-find-most-important-variables-r-amit-jain How to find the most important variables in R]
** [https://www.linkedin.com/pulse/how-find-most-important-variables-r-amit-jain How to find the most important variables in R]
** ?importance
** [https://www.r-bloggers.com/2012/07/random-forest-variable-importance/ Random Forest Variable Importance] and a simple example with 2 correlated predictors.
** [https://stackoverflow.com/a/35904266 If you just print the importance object from the model they are the raw importance values. However, when you use the importance function, the default for the scale argument is TRUE which returns the importance values divided by the standard error. ]
** [https://stats.stackexchange.com/a/12609 Measures of variable importance in random forests]
** [https://stackoverflow.com/a/39880068 Difference between varImp (caret) and importance (randomForest) for Random Forest]
** [https://avikarn.com/2020-06-26-MachineLearning_rf_glmnet/ Utilizing Machine Learning algorithms (GLMnet and Random Forest models) for Genomic Prediction of a Quantitative trait]
* [https://link.springer.com/article/10.1186/1471-2105-7-3 Gene selection and classification of microarray data using random forest] 2006, and the R package [https://cran.r-project.org/web/packages/varSelRF/ varSelRF]
* [https://link.springer.com/article/10.1186/1471-2105-7-3 Gene selection and classification of microarray data using random forest] 2006, and the R package [https://cran.r-project.org/web/packages/varSelRF/ varSelRF]



Revision as of 14:27, 9 October 2022