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traineR (version 2.2.10)

Predictive (Classification and Regression) Models Homologator

Description

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 García (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) .

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Version

Install

install.packages('traineR')

Monthly Downloads

435

Version

2.2.10

License

GPL (>= 2)

Maintainer

Oldemar Rodriguez

Last Published

January 17th, 2026

Functions in traineR (2.2.10)

original_model

original_model
print.indexes.prmdt

Printing prmdt index object
plot.prmdt

Plotting prmdt models
predict.svm.prmdt

predict.svm.prmdt
predict.randomForest.prmdt

predict.randomForest.prmdt
train.knn

train.knn
predict.nnet.prmdt

predict.nnet.prmdt
predict.qda.prmdt

predict.qda.prmdt
predict.rpart.prmdt

predict.rpart.prmdt
predict.neuralnet.prmdt

predict.neuralnet.prmdt
train.glmnet

train.glmnet
select_on_class

select_on_class
print.prediction.prmdt

Printing prmdt prediction object
varplot

Plotting prmdt ada models
train.bayes

train.bayes
train.adabag

train.adabag
predict.gbm.prmdt

predict.gbm.prmdt
predict.bayes.prmdt

predict.bayes.prmdt
train.ada

train.ada
train.qda

train.qda
train.nnet

train.nnet
traineR

Predictive (Classification and Regression) Models Homologator
prediction.variable.balance

prediction.variable.balance
train.rpart

train.rpart
train.lda

train.lda
train.neuralnet

train.neuralnet
predict.adabag.prmdt

predict.adabag.prmdt
predict.xgb.Booster.prmdt

predict.xgb.Booster
train.xgboost

train.xgboost
train.svm

train.svm
train.randomForest

train.randomForest
type_correction

type_correction
predict.glmnet.prmdt

predict.glmnet.prmdt
predict.glm.prmdt

predict.glm.prmdt
importance.plot

importance.plot
max_col

max_col
print.prmdt

Printing prmdt models
scaler

scaler
train.glm

train.glm
train.gbm

train.gbm
create.prediction

create.prediction
ROC.plot

ROC.plot
ROC.area

ROC.area
contr.dummy

contr.dummy
contr.metric

contr.metric
categorical.predictive.power

categorical.predictive.power
contr.ordinal

contr.ordinal
confusion.matrix

confusion.matrix
numerical.predictive.power

numerical.predictive.power
general.indexes

general.indexes
dummy.data.frame

dummy.data.frame
get_test_less_predict

get_test_less_predict
create.model

create.model
gg_color

gg_color
get.default.parameters

get.default.parameters
numeric_to_predict

numeric_to_predict
predict.ada.prmdt

predict.ada.prmdt
predict.knn.prmdt

predict.knn.prmdt
predict.lda.prmdt

predict.lda.prmdt