{"id":13468946,"url":"https://github.com/bearloga/maltese","last_synced_at":"2025-09-21T02:01:36.058Z","repository":{"id":65257691,"uuid":"80256373","full_name":"bearloga/maltese","owner":"bearloga","description":"Little R utility package for making time series data more machine learning-friendly","archived":false,"fork":false,"pushed_at":"2020-03-06T17:42:53.000Z","size":833,"stargazers_count":49,"open_issues_count":3,"forks_count":8,"subscribers_count":6,"default_branch":"master","last_synced_at":"2025-07-17T13:45:20.199Z","etag":null,"topics":["forecasting","machine-learning","r","r-package","rstats","time-series"],"latest_commit_sha":null,"homepage":"https://bearloga.github.io/maltese/neuralnet.html","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/bearloga.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2017-01-28T00:02:01.000Z","updated_at":"2025-01-14T15:50:29.000Z","dependencies_parsed_at":"2023-01-16T15:00:35.604Z","dependency_job_id":null,"html_url":"https://github.com/bearloga/maltese","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/bearloga/maltese","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bearloga%2Fmaltese","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bearloga%2Fmaltese/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bearloga%2Fmaltese/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bearloga%2Fmaltese/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/bearloga","download_url":"https://codeload.github.com/bearloga/maltese/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bearloga%2Fmaltese/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":276183774,"owners_count":25599223,"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","status":"online","status_checked_at":"2025-09-21T02:00:07.055Z","response_time":72,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["forecasting","machine-learning","r","r-package","rstats","time-series"],"created_at":"2024-07-31T15:01:22.428Z","updated_at":"2025-09-21T02:01:35.189Z","avatar_url":"https://github.com/bearloga.png","language":"R","readme":"# maltese: machine learning for time series\n\n[![Build Status](https://travis-ci.org/bearloga/maltese.svg?branch=master)](https://travis-ci.org/bearloga/maltese)\n\n## Installing\n\n```R\n# install.packages(\"remotes\")\nremotes::install_github(\"bearloga/maltese\")\n```\n\n## Example\n\n### Data\n\nThe included dataset is a tidy time series of pageviews for R's article on English Wikipedia from 2015-10-01 to 2017-01-30.\n\n```R\nlibrary(maltese)\nhead(r_enwiki)\n```\n\n|date       | pageviews|\n|:----------|---------:|\n|2015-10-01 |      3072|\n|2015-10-02 |      2575|\n|2015-10-03 |      1431|\n|2015-10-04 |      1540|\n|2015-10-05 |      3041|\n|2015-10-06 |      3695|\n\nWe can use `mlts_transform` to convert the data into a machine learning-friendly format with a 7-day lag:\n\n```R\nmlts \u003c- mlts_transform(\n  r_enwiki, date, pageviews,\n  p = 7, # how many previous points of data to use as features\n  granularity = \"day\", # optional, can be automatically detected,\n  extras = TRUE, extrasAsFactors = TRUE # FALSE by default :D\n)\nhead(mlts)\n```\n\n|dt         |    y|mlts_extras_monthday |mlts_extras_weekday |mlts_extras_week |mlts_extras_month |mlts_extras_year | mlts_lag_1| mlts_lag_2| mlts_lag_3| mlts_lag_4| mlts_lag_5| mlts_lag_6| mlts_lag_7|\n|:----------|----:|:--------------------|:-------------------|:----------------|:-----------------|:----------------|----------:|----------:|----------:|----------:|----------:|----------:|----------:|\n|2015-10-08 | 3278|8                    |Thursday            |41               |October           |2015             |       3385|       3695|       3041|       1540|       1431|       2575|       3072|\n|2015-10-09 | 2886|9                    |Friday              |41               |October           |2015             |       3278|       3385|       3695|       3041|       1540|       1431|       2575|\n|2015-10-10 | 1692|10                   |Saturday            |41               |October           |2015             |       2886|       3278|       3385|       3695|       3041|       1540|       1431|\n|2015-10-11 | 1902|11                   |Sunday              |41               |October           |2015             |       1692|       2886|       3278|       3385|       3695|       3041|       1540|\n|2015-10-12 | 3030|12                   |Monday              |41               |October           |2015             |       1902|       1692|       2886|       3278|       3385|       3695|       3041|\n|2015-10-13 | 3245|13                   |Tuesday             |41               |October           |2015             |       3030|       1902|       1692|       2886|       3278|       3385|       3695|\n\n### Results\n\n![Example forecast using a neural network](https://github.com/bearloga/maltese/raw/master/neuralnet.png)\n\nSee [the vignette](https://bearloga.github.io/maltese/neuralnet.html) for a detailed walkthrough.\n\n## Additional Information\n\nUsers of _maltese_ may also be interested in _[timetk](https://business-science.github.io/timetk/)_ ([available on CRAN](https://cran.r-project.org/package=timetk)) which provides several utility functions for working with and manipulating time series data into a ML-friendly form.\n\nPlease note that this project is released with a [Contributor Code of Conduct](https://github.com/bearloga/maltese/blob/master/CONDUCT.md). By participating in this project you agree to abide by its terms.\n","funding_links":[],"categories":["R"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbearloga%2Fmaltese","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbearloga%2Fmaltese","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbearloga%2Fmaltese/lists"}