Predictive (Classification and Regression) Models Homologator

Methods to unify the different ways of creating predictive models and their different predictive formats for classification and regression. It includes methods such as K-Nearest Neighbors Schliep, K. P. (2004) , Decision Trees Leo Breiman, Jerome H. Friedman, Richard A. Olshen, Charles J. Stone (2017) , ADA Boosting Esteban Alfaro, Matias Gamez, Noelia GarcĂ­a (2013) , Extreme Gradient Boosting Chen & Guestrin (2016) , Random Forest Breiman (2001) , Neural Networks Venables, W. N., & Ripley, B. D. (2002) , Support Vector Machines Bennett, K. P. & Campbell, C. (2000) , Bayesian Methods Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (1995) , Linear Discriminant Analysis Venables, W. N., & Ripley, B. D. (2002) , Quadratic Discriminant Analysis Venables, W. N., & Ripley, B. D. (2002) , Logistic Regression Dobson, A. J., & Barnett, A. G. (2018) and Penalized Logistic Regression Friedman, J. H., Hastie, T., & Tibshirani, R. (2010) .


Reference manual

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install.packages("traineR")

2.2.12 by Oldemar Rodriguez R., 7 months ago


https://promidat.website/


Report a bug at https://github.com/PROMiDAT/traineR/issues


Browse source code at https://github.com/cran/traineR


Authors: Oldemar Rodriguez R. [aut, cre] , Andres Navarro D. [aut] , Ariel Arroyo S. [aut] , Diego Jimenez A. [aut] , Jennifer Lobo V. [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports neuralnet, rpart, xgboost, randomForest, e1071, kknn, dplyr, MASS, nnet, stringr, rlang, adabag, glmnet, ROCR, gbm, ggplot2

Suggests rgl


Imported by predictoR, regressoR.


See at CRAN