I'm trying to ensemble a random forest with logistic regresion with H2O in R. However, an error messages appears in the following code:
> localH2O = h2o.init()
Successfully connected to http://137.0.0.1:43329/
R is connected to the H2O cluster:
H2O cluster uptime: 3 hours 11 minutes
H2O cluster version: 3.2.0.3
H2O cluster name: H2O_started_from_R_toshiba_jvd559
H2O cluster total nodes: 1
H2O cluster total memory: 0.97 GB
H2O cluster total cores: 4
H2O cluster allowed cores: 2
H2O cluster healthy: TRUE
>
> # defining the training data and set data for H2O
>
> training_frame <- as.h2o(localH2O, muestra.fullarbol)
|=========================================================================================| 100%
> validation_frame <- as.h2o(localH2O, test.fullarbol)
|=========================================================================================| 100%
>
> yn <- "ex"
> xn <- names(datafullarbol[,-c(1,2,3,9,10,11,12,17,19,20,21,22,23,24,29,31,32,33,34,35,36,47)])
>
>
>
>
> learner <- c("h2o.glm.wrapper", "h2o.randomForest.wrapper")
> metalearner <- "SL.glm"
> family <- "binomial"
>
> fit <- h2o.ensemble(x=xn, y=yn,training_frame = training_frame, family = family,
+ learner = learner, metalearner = metalearner,cvControl = list(V = 5))
|=========================================================================================| 100%
[1] "Cross-validating and training base learner 1: h2o.glm.wrapper"
|=========================================================================================| 100%
[1] "Cross-validating and training base learner 2: h2o.randomForest.wrapper"
|=========================================================================================| 100%
Error in h2o.cbind(predlist) :
`h2o.cbind` accepts only of H2OFrame objects
Apperently my parameters are given correctly , but as you see, the message: h2o.cbind accepts only of H2OFrame objects appears
. What could be the reason of the error?