revdep/checks.noindex/caretEnsemble/new/caretEnsemble.Rcheck/caretEnsemble-Ex.R

In gbm-developers/gbm: Generalized Boosted Regression Models

pkgname <- "caretEnsemble"
source(file.path(R.home("share"), "R", "examples-header.R"))
options(warn = 1)
library('caretEnsemble')

base::assign(".oldSearch", base::search(), pos = 'CheckExEnv')
base::assign(".old_wd", base::getwd(), pos = 'CheckExEnv')
cleanEx()
nameEx("autoplot")
### * autoplot

flush(stderr()); flush(stdout())

### Name: autoplot
### Title: Convenience function for more in-depth diagnostic plots of
###   caretEnsemble objects
### Aliases: autoplot

### ** Examples

## Not run: 
##D set.seed(42)
##D models <- caretList(
##D  iris[1:50,1:2],
##D  iris[1:50,3],
##D  trControl=trainControl(method="cv"),
##D  methodList=c("glm", "rpart"))
##D ens <- caretEnsemble(models)
##D autoplot(ens)
## End(Not run)



cleanEx()
nameEx("c.caretList")
### * c.caretList

flush(stderr()); flush(stdout())

### Name: c.caretList
### Title: S3 definition for concatenating caretList
### Aliases: c.caretList

### ** Examples

## Not run: 
##D  model_list1 <- caretList(Class ~ .,
##D   data=Sonar, trControl = ctrl1,
##D   tuneList = list(
##D                  glm=caretModelSpec(method='glm', family='binomial'),
##D                  rpart=caretModelSpec(method='rpart')
##D                  ),
##D    metric='ROC')
##D 
##D model_list2 <- caretList(Class ~ .,
##D                          data=Sonar,
##D                          trControl = ctrl1,
##D                          tuneList = list(
##D                            glm=caretModelSpec(method='rpart'),
##D                            rpart=caretModelSpec(method='rf')
##D                          ),
##D                          metric='ROC')
##D 
##D  bigList <- c(model_list1, model_list2)
## End(Not run)




cleanEx()
nameEx("c.train")
### * c.train

flush(stderr()); flush(stdout())

### Name: c.train
### Title: S3 definition for concatenating train objects
### Aliases: c.train

### ** Examples

## Not run: 
##D rpartTrain <- train(Class ~ .,
##D                     data=Sonar,
##D                     trControl = ctrl1,
##D                     method='rpart')
##D 
##D rfTrain <- train(Class ~ .,
##D                  data=Sonar,
##D                  trControl = ctrl1,
##D                  method='rf')
##D 
##D  bigList <- c(model_list1, model_list2)
## End(Not run)




cleanEx()
nameEx("caretEnsemble")
### * caretEnsemble

flush(stderr()); flush(stdout())

### Name: caretEnsemble
### Title: caretEnsemble: Make ensembles of caret models.
### Aliases: caretEnsemble caretEnsemble-package

### ** Examples

## Not run: 
##D set.seed(42)
##D models <- caretList(iris[1:50,1:2], iris[1:50,3], methodList=c("glm", "lm"))
##D ens <- caretEnsemble(models)
##D summary(ens)
## End(Not run)



cleanEx()
nameEx("caretList")
### * caretList

flush(stderr()); flush(stdout())

### Name: caretList
### Title: Create a list of several train models from the caret package
###   Build a list of train objects suitable for ensembling using the
###   'caretEnsemble' function.
### Aliases: caretList

### ** Examples

## Not run: 
##D myControl <- trainControl(method="cv", number=5)
##D caretList(
##D   Sepal.Length ~ Sepal.Width,
##D   head(iris, 50),
##D   methodList=c("glm", "lm"),
##D   trControl=myControl
##D   )
##D caretList(
##D   Sepal.Length ~ Sepal.Width,
##D   head(iris, 50), methodList=c("lm"),
##D   tuneList=list(
##D     nnet=caretModelSpec(method="nnet", trace=FALSE, tuneLength=1)
##D  ),
##D   trControl=myControl
##D   )
##D   
## End(Not run)



cleanEx()
nameEx("caretModelSpec")
### * caretModelSpec

flush(stderr()); flush(stdout())

### Name: caretModelSpec
### Title: Generate a specification for fitting a caret model
### Aliases: caretModelSpec

### ** Examples

caretModelSpec("rf", tuneLength=5, preProcess="ica")



cleanEx()
nameEx("caretStack")
### * caretStack

flush(stderr()); flush(stdout())

### Name: caretStack
### Title: Combine several predictive models via stacking
### Aliases: caretStack

### ** Examples

## Not run: 
##D library("rpart")
##D models <- caretList(
##D   x=iris[1:50,1:2],
##D   y=iris[1:50,3],
##D   trControl=trainControl(method="cv"),
##D   methodList=c("rpart", "glm")
##D )
##D caretStack(models, method="glm")
## End(Not run)



cleanEx()
nameEx("dotplot.caretStack")
### * dotplot.caretStack

flush(stderr()); flush(stdout())

### Name: dotplot.caretStack
### Title: Comparison dotplot for a caretStack object
### Aliases: dotplot.caretStack

### ** Examples

## Not run: 
##D set.seed(42)
##D library("rpart")
##D models <- caretList(
##D   x=iris[1:100,1:2],
##D   y=iris[1:100,3],
##D   trControl=trainControl(method="cv"),
##D   methodList=c("rpart", "glm")
##D )
##D meta_model <- caretStack(models, method="lm", trControl=trainControl(method="cv"))
##D dotplot.caretStack(meta_model)
## End(Not run)



cleanEx()
nameEx("plot.caretEnsemble")
### * plot.caretEnsemble

flush(stderr()); flush(stdout())

### Name: plot.caretEnsemble
### Title: Plot Diagnostics for an caretEnsemble Object
### Aliases: plot.caretEnsemble

### ** Examples

## Not run: 
##D set.seed(42)
##D models <- caretList(iris[1:50,1:2], iris[1:50,3], methodList=c("glm", "rpart"))
##D ens <- caretEnsemble(models)
##D plot(ens)
## End(Not run)



cleanEx()
nameEx("plot.caretStack")
### * plot.caretStack

flush(stderr()); flush(stdout())

### Name: plot.caretStack
### Title: Plot a caretStack object
### Aliases: plot.caretStack

### ** Examples

## Not run: 
##D library("rpart")
##D models <- caretList(
##D   x=iris[1:100,1:2],
##D   y=iris[1:100,3],
##D   trControl=trainControl(method="cv"),
##D   methodList=c("rpart", "glm")
##D )
##D meta_model <- caretStack(models, method="rpart", tuneLength=2)
##D plot(meta_model)
## End(Not run)



cleanEx()
nameEx("predict.caretStack")
### * predict.caretStack

flush(stderr()); flush(stdout())

### Name: predict.caretStack
### Title: Make predictions from a caretStack
### Aliases: predict.caretStack

### ** Examples

## Not run: 
##D library("rpart")
##D models <- caretList(
##D   x=iris[1:100,1:2],
##D   y=iris[1:100,3],
##D   trControl=trainControl(method="cv"),
##D   methodList=c("rpart", "glm")
##D )
##D meta_model <- caretStack(models, method="lm")
##D RMSE(predict(meta_model, iris[101:150,1:2]), iris[101:150,3])
## End(Not run)



cleanEx()
nameEx("print.caretStack")
### * print.caretStack

flush(stderr()); flush(stdout())

### Name: print.caretStack
### Title: Print a caretStack object
### Aliases: print.caretStack

### ** Examples

## Not run: 
##D library("rpart")
##D models <- caretList(
##D   x=iris[1:100,1:2],
##D   y=iris[1:100,3],
##D   trControl=trainControl(method="cv"),
##D   methodList=c("rpart", "glm")
##D )
##D meta_model <- caretStack(models, method="lm")
##D print(meta_model)
## End(Not run)



cleanEx()
nameEx("summary.caretEnsemble")
### * summary.caretEnsemble

flush(stderr()); flush(stdout())

### Name: summary.caretEnsemble
### Title: Summarize the results of caretEnsemble for the user.
### Aliases: summary.caretEnsemble

### ** Examples

## Not run: 
##D set.seed(42)
##D models <- caretList(iris[1:50,1:2], iris[1:50,3], methodList=c("glm", "lm"))
##D ens <- caretEnsemble(models)
##D summary(ens)
## End(Not run)



cleanEx()
nameEx("summary.caretStack")
### * summary.caretStack

flush(stderr()); flush(stdout())

### Name: summary.caretStack
### Title: Summarize a caretStack object
### Aliases: summary.caretStack

### ** Examples

## Not run: 
##D library("rpart")
##D models <- caretList(
##D   x=iris[1:100,1:2],
##D   y=iris[1:100,3],
##D   trControl=trainControl(method="cv"),
##D   methodList=c("rpart", "glm")
##D )
##D meta_model <- caretStack(models, method="lm")
##D summary(meta_model)
## End(Not run)



### * <FOOTER>
###
cleanEx()
options(digits = 7L)
base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")
grDevices::dev.off()
###
### Local variables: ***
### mode: outline-minor ***
### outline-regexp: "\\(> \\)?### [*]+" ***
### End: ***
quit('no')