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Microeconometric analysis of social housing in Austria.

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MicEcon

CRAN status Lifecycle: experimental

The goal of MicEcon is to …

Installation

if(!require(devtools)){
install.packages("devtools")
}

if(!require(catboost)){
devtools::install_github('catboost/catboost', subdir = 'catboost/R-package')
}

devtools::install_github("Akai01/MicEcon")

Example

This is a basic example which shows you how to solve a common problem:

# A toy example

library(MicEcon)

data(iris, package = "datasets")

fit <- auto_catboost_reg(
  iris,
  label_col_name = "Petal.Length",
  cat_features = "Species",
  has_time = FALSE,
  fold_count = 3,
  type = "Classical",
  partition_random_seed = 0,
  shuffle = TRUE,
  stratified = FALSE,
  early_stopping_rounds = NULL,
  iterations = list(lower = 100, upper = 110),
  learning_rate = list(lower = 0.001, upper = 0.05),
  l2_leaf_reg = list(lower = 0, upper = 5),
  depth = list(lower = 1, upper = 10),
  bagging_temperature = list(lower = 0, upper = 100),
  rsm = list(lower = 0, upper = 1),
  border_count = list(lower = 1, upper = 254),
   logging_level = 'Silent',
  bo_iters = 2
)
#> Loading required namespace: catboost


varimp <- get_var_imp(fit$model)

plot_varimp(varimp)

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