{"id":18407474,"url":"https://github.com/akai01/micecon","last_synced_at":"2025-10-12T20:17:21.754Z","repository":{"id":130004453,"uuid":"241901914","full_name":"Akai01/MicEcon","owner":"Akai01","description":"Microeconometric analysis of social housing in Austria.","archived":false,"fork":false,"pushed_at":"2021-01-07T08:38:56.000Z","size":75,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-12T21:14:07.267Z","etag":null,"topics":["automl","bayesian-optimization","boosting-algorithms","microeconometrics","r"],"latest_commit_sha":null,"homepage":"","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Akai01.png","metadata":{"files":{"readme":"README.Rmd","changelog":"NEWS.md","contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-02-20T14:15:24.000Z","updated_at":"2021-01-11T11:57:58.000Z","dependencies_parsed_at":null,"dependency_job_id":"d4a070f2-f86e-4694-843f-67aebab0c0c2","html_url":"https://github.com/Akai01/MicEcon","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akai01%2FMicEcon","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akai01%2FMicEcon/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akai01%2FMicEcon/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akai01%2FMicEcon/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Akai01","download_url":"https://codeload.github.com/Akai01/MicEcon/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248631682,"owners_count":21136562,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["automl","bayesian-optimization","boosting-algorithms","microeconometrics","r"],"created_at":"2024-11-06T03:14:08.334Z","updated_at":"2025-10-12T20:17:16.714Z","avatar_url":"https://github.com/Akai01.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"---\noutput: github_document\n---\n\n\u003c!-- README.md is generated from README.Rmd. Please edit that file --\u003e\n\n```{r, include = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/README-\",\n  out.width = \"100%\"\n)\n```\n\n# MicEcon\n\n\u003c!-- badges: start --\u003e\n[![CRAN status](https://www.r-pkg.org/badges/version/MicEcon)](https://CRAN.R-project.org/package=MicEcon)\n[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)\n\u003c!-- badges: end --\u003e\n\nThe goal of MicEcon is to ...\n\n## Installation\n\n\n``` r\nif(!require(devtools)){\ninstall.packages(\"devtools\")\n}\n\nif(!require(catboost)){\ndevtools::install_github('catboost/catboost', subdir = 'catboost/R-package')\n}\n\ndevtools::install_github(\"Akai01/MicEcon\")\n```\n## Example\n\nThis is a basic example which shows you how to solve a common problem:\n\n```{r example}\n# A toy example\n\nlibrary(MicEcon)\n\ndata(iris, package = \"datasets\")\n\nfit \u003c- auto_catboost_reg(\n  iris,\n  label_col_name = \"Petal.Length\",\n  cat_features = \"Species\",\n  has_time = FALSE,\n  fold_count = 3,\n  type = \"Classical\",\n  partition_random_seed = 0,\n  shuffle = TRUE,\n  stratified = FALSE,\n  early_stopping_rounds = NULL,\n  iterations = list(lower = 100, upper = 110),\n  learning_rate = list(lower = 0.001, upper = 0.05),\n  l2_leaf_reg = list(lower = 0, upper = 5),\n  depth = list(lower = 1, upper = 10),\n  bagging_temperature = list(lower = 0, upper = 100),\n  rsm = list(lower = 0, upper = 1),\n  border_count = list(lower = 1, upper = 254),\n   logging_level = 'Silent',\n  bo_iters = 2\n)\n\n\nvarimp \u003c- get_var_imp(fit$model)\n\nplot_varimp(varimp)\n\n```\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fakai01%2Fmicecon","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fakai01%2Fmicecon","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fakai01%2Fmicecon/lists"}