Problems with Date

[alexeks]

Modeltimeh2o error is

_Error in .h2o.doSafeREST(h2oRestApiVersion = h2oRestApiVersion, urlSuffix = page, : ERROR MESSAGE: Provided column type POSIXct is unknown. Cannot proceed with parse due to invalid argument._ If the Date is passed as a date (without minutes ann seconds) there is no error message

h2o code itself is running with minutes and seconds with no problems. Both codes are below. The data file is attached.

library(modeltime) library(modeltime.h2o) library(modeltime.resample) library(modeltime.ensemble) library(timetk) library(tidymodels) library(tidyverse) library(dplyr) library(tidyr) library(lubridate) h20.csv

h2o code without modeltime h2o

h2o.init( nthreads = -1, ip = 'localhost', port = 54321 )

h2odf1<-h2o.importFile("C:/City of Chico/h20.csv")

aml <- h2o.automl(x = "Date", y = "total", training_frame = h2odf1, max_models = 20, seed = 1)

lb <- aml@leaderboard print(lb, n = nrow(lb))

modeltime h2o code

h2o.init( nthreads = -1, ip = 'localhost', port = 54321 )

model_spec <- automl_reg(mode = 'regression') %>% set_engine( engine = 'h2o', max_runtime_secs = 5, max_runtime_secs_per_model = 3, max_models = 3, nfolds = 5, exclude_algos = c("DeepLearning"), verbosity = NULL, seed = 786 )

model_fitted1 <- model_spec %>% fit(total ~ Date,data=as.data.frame(h2odf1))

[mdancho84]

Will take a look and let you know.

[ichsan2895]

Modeltimeh2o error is

_Error in .h2o.doSafeREST(h2oRestApiVersion = h2oRestApiVersion, urlSuffix = page, : ERROR MESSAGE: Provided column type POSIXct is unknown. Cannot proceed with parse due to invalid argument._ If the Date is passed as a date (without minutes ann seconds) there is no error message

h2o code itself is running with minutes and seconds with no problems.

Both codes are below. The data file is attached. library(modeltime) library(modeltime.h2o) library(modeltime.resample) library(modeltime.ensemble) library(timetk) library(tidymodels) library(tidyverse) library(dplyr) library(tidyr) library(lubridate) h20.csv

h2o code without modeltime h2o

h2o.init( nthreads = -1, ip = 'localhost', port = 54321 )

h2odf1<-h2o.importFile("C:/City of Chico/h20.csv")

aml <- h2o.automl(x = "Date", y = "total", training_frame = h2odf1, max_models = 20, seed = 1)

lb <- aml@leaderboard print(lb, n = nrow(lb))

modeltime h2o code

h2o.init( nthreads = -1, ip = 'localhost', port = 54321 )

model_spec <- automl_reg(mode = 'regression') %>% set_engine( engine = 'h2o', max_runtime_secs = 5, max_runtime_secs_per_model = 3, max_models = 3, nfolds = 5, exclude_algos = c("DeepLearning"), verbosity = NULL, seed = 786 )

model_fitted1 <- model_spec %>% fit(total ~ Date,data=as.data.frame(h2odf1))

you can try h2odf1_rev <- h2odf1 %>% mutate(Date = as.Date(Date))

then, you use that dataframe in this syntax model_fitted1 <- model_spec %>% fit(total ~ Date, data=h2odf1_rev)