# This R environment comes with all of CRAN preinstalled, as well as many other helpful packages
# The environment is defined by the kaggle/rstats docker image: https://github.com/kaggle/docker-rstats
# For example, here's several helpful packages to load in 

library(ggplot2) # Data visualization
library(data.table)
library(h2o)
h2o.init()
# Input data files are available in the "../input/" directory.
# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory

#clicks_test<-fread("../input/clicks_test.csv", header = TRUE)
#documents_categories<-fread("../input/documents_categories.csv", header = TRUE)
#documents_entities<-fread("../input/documents_entities.csv", header = TRUE)
#documents_meta<-fread("../input/documents_meta.csv", header = TRUE)
#documents_topics<-fread("../input/documents_topics.csv", header = TRUE)
#events<-fread("../input/events.csv", header = TRUE)
#page_views_samole<-fread("../input/page_views_samole.csv", header = TRUE)
#promoted_content<-fread("../input/promoted_content.csv", header = TRUE)
#clicks_train<-fread("../input/clicks_train.csv", header = TRUE)
#sample_submission<-fread("../input/sample_submission.csv", header = TRUE)


# Any results you write to the current directory are saved as output.