The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
You can install the development version of randomMachines from GitHub with:
# install.packages("devtools")
::install_github("MateusMaiaDS/randomMachines") devtools
This is a basic example which shows you how to solve a common binary classification problem:
library(randomMachines)
## Simple classification example
<- randomMachines::sim_class(n=100)
sim_train <- randomMachines::sim_class(n=100)
sim_test <- randomMachines::randomMachines(y~.,train = sim_train, B = 25,prob_model = F)
rm_mod <- predict(rm_mod,sim_test) rm_mod_pred
For a regression task we would have similarly
library(randomMachines)
## Simple regression example
<- randomMachines::sim_reg1(n=100)
sim_train <- randomMachines::sim_reg1(n=100)
sim_test <- randomMachines::randomMachines(y~.,train = sim_train,B = 25)
rm_mod <- predict(rm_mod,sim_test) rm_mod_pred
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.