Maintainer: ‘Nailong Zhang <setseed2016@gmail.com>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: person(given = "Nailong",
                    family = "Zhang",
                    role = c("aut", "cre"),
                    email = "setseed2016@gmail.com")
as necessary.
Running examples in ‘dblr-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: dblr_train
> ### Title: Discrete Boosting Logistic Regression Training
> ### Aliases: dblr_train
> 
> ### ** Examples
> 
> # use iris data for example
> dat <- iris
> # create two categorical variables
> dat$Petal.Width <- as.factor((iris$Petal.Width<=0.2)*1+(iris$Petal.Width>1.0)*2)
> dat$Sepal.Length <- (iris$Sepal.Length<=3.0)*2+(iris$Sepal.Length>6.0)*1.25
> # create the response variable
> dat$Species <- as.numeric(dat$Species=='versicolor')
> set.seed(123)
> # random sampling
> index <- sample(1:150,100,replace = FALSE)
> # train the dblr model using the training data
> dblr_fit <- dblr_train(train_x=dat[index,c(1:4)],
+ train_y=dat[index,5],category_cols = c('Petal.Width','Sepal.Length'),
+ metric = 'logloss',subsample = 0.5,eta = 0.05,colsample = 1.0,
+ lambda = 1.0,cv_early_stops = 10,verbose=FALSE)
Warning in throw_err_or_depr_msg("Passed unrecognized parameters: ", paste(head(names_unrecognized),  :
  Passed unrecognized parameters: metrics. This warning will become an error in a future version.
Error in begin_iteration:end_iteration : argument of length 0
Calls: dblr_train -> <Anonymous>
Execution halted
Maintainer: ‘Nailong Zhang <setseed2016@gmail.com>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: person(given = "Nailong",
                    family = "Zhang",
                    role = c("aut", "cre"),
                    email = "setseed2016@gmail.com")
as necessary.
Running examples in ‘dblr-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: dblr_train
> ### Title: Discrete Boosting Logistic Regression Training
> ### Aliases: dblr_train
> 
> ### ** Examples
> 
> # use iris data for example
> dat <- iris
> # create two categorical variables
> dat$Petal.Width <- as.factor((iris$Petal.Width<=0.2)*1+(iris$Petal.Width>1.0)*2)
> dat$Sepal.Length <- (iris$Sepal.Length<=3.0)*2+(iris$Sepal.Length>6.0)*1.25
> # create the response variable
> dat$Species <- as.numeric(dat$Species=='versicolor')
> set.seed(123)
> # random sampling
> index <- sample(1:150,100,replace = FALSE)
> # train the dblr model using the training data
> dblr_fit <- dblr_train(train_x=dat[index,c(1:4)],
+ train_y=dat[index,5],category_cols = c('Petal.Width','Sepal.Length'),
+ metric = 'logloss',subsample = 0.5,eta = 0.05,colsample = 1.0,
+ lambda = 1.0,cv_early_stops = 10,verbose=FALSE)
Warning in throw_err_or_depr_msg("Passed unrecognized parameters: ", paste(head(names_unrecognized),  :
  Passed unrecognized parameters: metrics. This warning will become an error in a future version.
Error in begin_iteration:end_iteration : argument of length 0
Calls: dblr_train -> <Anonymous>
Execution halted
Running examples in ‘dblr-Ex.R’ failed
The error most likely occurred in:

> ### Name: dblr_train
> ### Title: Discrete Boosting Logistic Regression Training
> ### Aliases: dblr_train
> 
> ### ** Examples
> 
> # use iris data for example
> dat <- iris
> # create two categorical variables
> dat$Petal.Width <- as.factor((iris$Petal.Width<=0.2)*1+(iris$Petal.Width>1.0)*2)
> dat$Sepal.Length <- (iris$Sepal.Length<=3.0)*2+(iris$Sepal.Length>6.0)*1.25
> # create the response variable
> dat$Species <- as.numeric(dat$Species=='versicolor')
> set.seed(123)
> # random sampling
> index <- sample(1:150,100,replace = FALSE)
> # train the dblr model using the training data
> dblr_fit <- dblr_train(train_x=dat[index,c(1:4)],
+ train_y=dat[index,5],category_cols = c('Petal.Width','Sepal.Length'),
+ metric = 'logloss',subsample = 0.5,eta = 0.05,colsample = 1.0,
+ lambda = 1.0,cv_early_stops = 10,verbose=FALSE)
Warning in throw_err_or_depr_msg("Passed unrecognized parameters: ", paste(head(names_unrecognized),  :
  Passed unrecognized parameters: metrics. This warning will become an error in a future version.
Error in if (nrounds == 0) iteration <- end_iteration : 
  argument is of length zero
Calls: dblr_train -> <Anonymous>
Execution halted
Running examples in ‘dblr-Ex.R’ failed
The error most likely occurred in:

> ### Name: dblr_train
> ### Title: Discrete Boosting Logistic Regression Training
> ### Aliases: dblr_train
> 
> ### ** Examples
> 
> # use iris data for example
> dat <- iris
> # create two categorical variables
> dat$Petal.Width <- as.factor((iris$Petal.Width<=0.2)*1+(iris$Petal.Width>1.0)*2)
> dat$Sepal.Length <- (iris$Sepal.Length<=3.0)*2+(iris$Sepal.Length>6.0)*1.25
> # create the response variable
> dat$Species <- as.numeric(dat$Species=='versicolor')
> set.seed(123)
> # random sampling
> index <- sample(1:150,100,replace = FALSE)
> # train the dblr model using the training data
> dblr_fit <- dblr_train(train_x=dat[index,c(1:4)],
+ train_y=dat[index,5],category_cols = c('Petal.Width','Sepal.Length'),
+ metric = 'logloss',subsample = 0.5,eta = 0.05,colsample = 1.0,
+ lambda = 1.0,cv_early_stops = 10,verbose=FALSE)
Warning in throw_err_or_depr_msg("Passed unrecognized parameters: ", paste(head(names_unrecognized),  :
  Passed unrecognized parameters: metrics. This warning will become an error in a future version.
Error in if (nrounds == 0) iteration <- end_iteration : 
  argument is of length zero
Calls: dblr_train -> <Anonymous>
Execution halted
Running examples in 'dblr-Ex.R' failed
The error most likely occurred in:

> ### Name: dblr_train
> ### Title: Discrete Boosting Logistic Regression Training
> ### Aliases: dblr_train
> 
> ### ** Examples
> 
> # use iris data for example
> dat <- iris
> # create two categorical variables
> dat$Petal.Width <- as.factor((iris$Petal.Width<=0.2)*1+(iris$Petal.Width>1.0)*2)
> dat$Sepal.Length <- (iris$Sepal.Length<=3.0)*2+(iris$Sepal.Length>6.0)*1.25
> # create the response variable
> dat$Species <- as.numeric(dat$Species=='versicolor')
> set.seed(123)
> # random sampling
> index <- sample(1:150,100,replace = FALSE)
> # train the dblr model using the training data
> dblr_fit <- dblr_train(train_x=dat[index,c(1:4)],
+ train_y=dat[index,5],category_cols = c('Petal.Width','Sepal.Length'),
+ metric = 'logloss',subsample = 0.5,eta = 0.05,colsample = 1.0,
+ lambda = 1.0,cv_early_stops = 10,verbose=FALSE)
Warning in throw_err_or_depr_msg("Passed unrecognized parameters: ", paste(head(names_unrecognized),  :
  Passed unrecognized parameters: metrics. This warning will become an error in a future version.
Error in begin_iteration:end_iteration : argument of length 0
Calls: dblr_train -> <Anonymous>
Execution halted
Running examples in ‘dblr-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: dblr_train
> ### Title: Discrete Boosting Logistic Regression Training
> ### Aliases: dblr_train
> 
> ### ** Examples
> 
> # use iris data for example
> dat <- iris
> # create two categorical variables
> dat$Petal.Width <- as.factor((iris$Petal.Width<=0.2)*1+(iris$Petal.Width>1.0)*2)
> dat$Sepal.Length <- (iris$Sepal.Length<=3.0)*2+(iris$Sepal.Length>6.0)*1.25
> # create the response variable
> dat$Species <- as.numeric(dat$Species=='versicolor')
> set.seed(123)
> # random sampling
> index <- sample(1:150,100,replace = FALSE)
> # train the dblr model using the training data
> dblr_fit <- dblr_train(train_x=dat[index,c(1:4)],
+ train_y=dat[index,5],category_cols = c('Petal.Width','Sepal.Length'),
+ metric = 'logloss',subsample = 0.5,eta = 0.05,colsample = 1.0,
+ lambda = 1.0,cv_early_stops = 10,verbose=FALSE)
Warning in throw_err_or_depr_msg("Passed unrecognized parameters: ", paste(head(names_unrecognized),  :
  Passed unrecognized parameters: metrics. This warning will become an error in a future version.
Error in begin_iteration:end_iteration : argument of length 0
Calls: dblr_train -> <Anonymous>
Execution halted
Running examples in ‘dblr-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: dblr_train
> ### Title: Discrete Boosting Logistic Regression Training
> ### Aliases: dblr_train
> 
> ### ** Examples
> 
> # use iris data for example
> dat <- iris
> # create two categorical variables
> dat$Petal.Width <- as.factor((iris$Petal.Width<=0.2)*1+(iris$Petal.Width>1.0)*2)
> dat$Sepal.Length <- (iris$Sepal.Length<=3.0)*2+(iris$Sepal.Length>6.0)*1.25
> # create the response variable
> dat$Species <- as.numeric(dat$Species=='versicolor')
> set.seed(123)
> # random sampling
> index <- sample(1:150,100,replace = FALSE)
> # train the dblr model using the training data
> dblr_fit <- dblr_train(train_x=dat[index,c(1:4)],
+ train_y=dat[index,5],category_cols = c('Petal.Width','Sepal.Length'),
+ metric = 'logloss',subsample = 0.5,eta = 0.05,colsample = 1.0,
+ lambda = 1.0,cv_early_stops = 10,verbose=FALSE)
Warning in throw_err_or_depr_msg("Passed unrecognized parameters: ", paste(head(names_unrecognized),  :
  Passed unrecognized parameters: metrics. This warning will become an error in a future version.
Error in begin_iteration:end_iteration : argument of length 0
Calls: dblr_train -> <Anonymous>
Execution halted
Running examples in 'dblr-Ex.R' failed
The error most likely occurred in:

> ### Name: dblr_train
> ### Title: Discrete Boosting Logistic Regression Training
> ### Aliases: dblr_train
> 
> ### ** Examples
> 
> # use iris data for example
> dat <- iris
> # create two categorical variables
> dat$Petal.Width <- as.factor((iris$Petal.Width<=0.2)*1+(iris$Petal.Width>1.0)*2)
> dat$Sepal.Length <- (iris$Sepal.Length<=3.0)*2+(iris$Sepal.Length>6.0)*1.25
> # create the response variable
> dat$Species <- as.numeric(dat$Species=='versicolor')
> set.seed(123)
> # random sampling
> index <- sample(1:150,100,replace = FALSE)
> # train the dblr model using the training data
> dblr_fit <- dblr_train(train_x=dat[index,c(1:4)],
+ train_y=dat[index,5],category_cols = c('Petal.Width','Sepal.Length'),
+ metric = 'logloss',subsample = 0.5,eta = 0.05,colsample = 1.0,
+ lambda = 1.0,cv_early_stops = 10,verbose=FALSE)
Warning in throw_err_or_depr_msg("Passed unrecognized parameters: ", paste(head(names_unrecognized),  :
  Passed unrecognized parameters: metrics. This warning will become an error in a future version.
Error in begin_iteration:end_iteration : argument of length 0
Calls: dblr_train -> <Anonymous>
Execution halted
'LazyData' is specified without a 'data' directory
'LazyData' is specified without a 'data' directory
'LazyData' is specified without a 'data' directory
Running examples in 'dblr-Ex.R' failed
The error most likely occurred in:

> ### Name: dblr_train
> ### Title: Discrete Boosting Logistic Regression Training
> ### Aliases: dblr_train
> 
> ### ** Examples
> 
> # use iris data for example
> dat <- iris
> # create two categorical variables
> dat$Petal.Width <- as.factor((iris$Petal.Width<=0.2)*1+(iris$Petal.Width>1.0)*2)
> dat$Sepal.Length <- (iris$Sepal.Length<=3.0)*2+(iris$Sepal.Length>6.0)*1.25
> # create the response variable
> dat$Species <- as.numeric(dat$Species=='versicolor')
> set.seed(123)
> # random sampling
> index <- sample(1:150,100,replace = FALSE)
> # train the dblr model using the training data
> dblr_fit <- dblr_train(train_x=dat[index,c(1:4)],
+ train_y=dat[index,5],category_cols = c('Petal.Width','Sepal.Length'),
+ metric = 'logloss',subsample = 0.5,eta = 0.05,colsample = 1.0,
+ lambda = 1.0,cv_early_stops = 10,verbose=FALSE)
Warning in throw_err_or_depr_msg("Passed unrecognized parameters: ", paste(head(names_unrecognized),  :
  Passed unrecognized parameters: metrics. This warning will become an error in a future version.
Error in begin_iteration:end_iteration : argument of length 0
Calls: dblr_train -> <Anonymous>
Execution halted