shinyML_regression {shinyML} | R Documentation |
Implement a shiny web app to compare h2o and Spark supervised machine learning models for regression tasks
Description
This function creates in one line of code a shareable web app to compare supervised regression model performances
Usage
shinyML_regression(
data = data,
y,
framework = "h2o",
share_app = FALSE,
port = NULL
)
Arguments
data |
dataset containing one or more explanatory variables and one numeric variable to forecast. The dataset must be a data.frame or a data.table and can contain time-based column on Date or POSIXct format |
y |
the numerical output variable to forecast (must correspond to one data column) |
framework |
the machine learning framework chosen to train and test models (either h2o or Spark). h2o by default |
share_app |
a logical value indicating whether the app must be shared on local LAN |
port |
a four-digit number corresponding to the port the application should listen to. This parameter is necessary only if share_app option is set to TRUE |
Author(s)
Jean Bertin, jean.bertin@mines-paris.org
Examples
## Not run:
library(shinyML)
# Classical regression analysis
shinyML_regression(data = iris,y = "Petal.Width",framework = "h2o")
# Time series analysis
longley2 <- longley %>% mutate(Year = as.Date(as.character(Year),format = "%Y"))
shinyML_regression(data = longley2,y = "Population",framework = "h2o")
## End(Not run)