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traineR (version 2.2.12)

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

224

Version

2.2.12

License

GPL (>= 2)

Maintainer

Oldemar Rodriguez

Last Published

March 3rd, 2026

Functions in traineR (2.2.12)

predict.nnet.prmdt

predict.nnet.prmdt
predict.gbm.prmdt

predict.gbm.prmdt
predict.glm.prmdt

predict.glm.prmdt
predict.qda.prmdt

predict.qda.prmdt
get_test_less_predict

get_test_less_predict
print.prediction.prmdt

Printing prmdt prediction object
predict.adabag.prmdt

predict.adabag.prmdt
predict.svm.prmdt

predict.svm.prmdt
predict.bayes.prmdt

predict.bayes.prmdt
original_model

original_model
predict.glmnet.prmdt

predict.glmnet.prmdt
scaler

scaler
predict.knn.prmdt

predict.knn.prmdt
train.knn

train.knn
predict.xgb.Booster.prmdt

predict.xgb.Booster
plot.prmdt

Plotting prmdt models
confusion.matrix

confusion.matrix
train.glmnet

train.glmnet
select_on_class

select_on_class
predict.randomForest.prmdt

predict.randomForest.prmdt
numerical.predictive.power

numerical.predictive.power
train.adabag

train.adabag
prediction.variable.balance

prediction.variable.balance
numeric_to_predict

numeric_to_predict
print.indexes.prmdt

Printing prmdt index object
train.bayes

train.bayes
predict.rpart.prmdt

predict.rpart.prmdt
train.nnet

train.nnet
train.qda

train.qda
print.prmdt

Printing prmdt models
predict.neuralnet.prmdt

predict.neuralnet.prmdt
predict.lda.prmdt

predict.lda.prmdt
train.svm

train.svm
train.lda

train.lda
train.neuralnet

train.neuralnet
train.glm

train.glm
train.gbm

train.gbm
train.randomForest

train.randomForest
train.xgboost

train.xgboost
train.rpart

train.rpart
traineR

Predictive (Classification and Regression) Models Homologator
type_correction

type_correction
contr.ordinal

contr.ordinal
contr.metric

contr.metric
categorical.predictive.power

categorical.predictive.power
create.prediction

create.prediction
ROC.area

ROC.area
contr.dummy

contr.dummy
ROC.plot

ROC.plot
importance.plot

importance.plot
general.indexes

general.indexes
dummy.data.frame

dummy.data.frame
create.model

create.model
gg_color

gg_color
get.default.parameters

get.default.parameters
max_col

max_col