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traineR (version 2.0.4)

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

2.0.4

License

GPL (>= 2)

Maintainer

Oldemar Rodriguez

Last Published

August 22nd, 2022

Functions in traineR (2.0.4)

predict.gbm.prmdt

predict.gbm.prmdt
predict.bayes.prmdt

predict.bayes.prmdt
predict.adabag.prmdt

predict.adabag.prmdt
numeric_to_predict

numeric_to_predict
predict.nnet.prmdt

predict.nnet.prmdt
predict.lda.prmdt

predict.lda.prmdt
dummy.data.frame

dummy.data.frame
predict.glm.prmdt

predict.glm.prmdt
contr.dummy

contr.dummy
prediction.variable.balance

prediction.variable.balance
predict.qda.prmdt

predict.qda.prmdt
confusion.matrix

confusion.matrix
predict.randomForest.prmdt

predict.randomForest.prmdt
predict.neuralnet.prmdt

predict.neuralnet.prmdt
dummy

dummy
categorical.predictive.power

categorical.predictive.power
boosting.importance.plot

boosting.importance.plot
train.lda

train.lda
predict.rpart.prmdt

predict.rpart.prmdt
original_model

original_model
predict.svm.prmdt

predict.svm.prmdt
predict.knn.prmdt

predict.knn.prmdt
predict.glmnet.prmdt

predict.glmnet.prmdt
numerical.predictive.power

numerical.predictive.power
train.knn

train.knn
predict.xgb.Booster.prmdt

predict.xgb.Booster
varplot

Plotting prmdt ada models
train.glmnet

train.glmnet
print.indexes.prmdt

Printing prmdt index object
train.gbm

train.gbm
train.neuralnet

train.neuralnet
plot.prmdt

Plotting prmdt models
print.prediction.prmdt

Printing prmdt prediction object
predict.ada.prmdt

predict.ada.prmdt
train.rpart

train.rpart
print.prmdt

Printing prmdt models
train.ada

train.ada
train.randomForest

train.randomForest
train.nnet

train.nnet
traineR

Predictive (Classification and Regression) Models Homologator
train.qda

train.qda
train.svm

train.svm
train.glm

train.glm
train.bayes

train.bayes
train.adabag

train.adabag
select_on_class

select_on_class
get.default.parameters

get.default.parameters
train.xgboost

train.xgboost
type_correction

type_correction
ROC.area

ROC.area
contr.ordinal

contr.ordinal
create.model

create.model
contr.metric

contr.metric
ROC.plot

ROC.plot
create.prediction

create.prediction
max_col

max_col
general.indexes

general.indexes
get_test_less_predict

get_test_less_predict
gg_color

gg_color