{"id":15138126,"url":"https://github.com/ciwooooo/handwriting-classification","last_synced_at":"2026-02-14T03:09:56.786Z","repository":{"id":241590960,"uuid":"805417210","full_name":"Ciwooooo/handwriting-classification","owner":"Ciwooooo","description":"A time series classification challange. The point is to classifiy whether a child's handwriting is affected by dysgraphia. the features represent the movements of a pen on a tablet the child wrote on. ","archived":false,"fork":false,"pushed_at":"2024-05-28T15:58:37.000Z","size":1121,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-06T06:44:31.680Z","etag":null,"topics":["classification","handwriting","knn-classification","machine-learning","rocket","time-series"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/Ciwooooo.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-05-24T14:25:45.000Z","updated_at":"2024-05-28T15:58:40.000Z","dependencies_parsed_at":null,"dependency_job_id":"4a4286b6-144a-4aa7-996b-cff1bec2835b","html_url":"https://github.com/Ciwooooo/handwriting-classification","commit_stats":{"total_commits":6,"total_committers":1,"mean_commits":6.0,"dds":0.0,"last_synced_commit":"2b489af8f0a9dfa80a8e35839e7ffb5ea8c65e09"},"previous_names":["ciwooooo/handwriting-classification"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ciwooooo%2Fhandwriting-classification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ciwooooo%2Fhandwriting-classification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ciwooooo%2Fhandwriting-classification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ciwooooo%2Fhandwriting-classification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Ciwooooo","download_url":"https://codeload.github.com/Ciwooooo/handwriting-classification/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247445651,"owners_count":20939953,"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":["classification","handwriting","knn-classification","machine-learning","rocket","time-series"],"created_at":"2024-09-26T07:20:46.805Z","updated_at":"2025-09-21T17:37:06.707Z","avatar_url":"https://github.com/Ciwooooo.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Handwriting Classification Challange\n\nThis is a small time-series challenge I did during my master's. All credit for the challange idea goes to **Dr. Sharon Ong**, Department of Cognitive Science and Artificial Inteligence, Tilburg University.\n\n**Update:** My implementation of Rocket managed to win 2nd place in the competition :)\n\nThe objective of this challange is  to classify whether a child's handwriting is affected by dysgraphia. The data comes from the study by *Drotár and Dobeš, 2020* and is avaliable [here](https://github.com/peet292929/Dysgraphia-detection-through-machine-learning). It was collected using a using a WACOM Intuos Pro Large tablet.\nThe features are numeric and represent the below over time:\n\n* pen movement in the x-direction,\n* pen movement in the y-direction\n* whether the pen was on the surface (1) or in the air (0)\n* the pressure of the pen on the tablet surface\n* the azimuth of the pen on the tablet surface\n\n**References**\nDrotár, P., Dobeš, M. Dysgraphia detection through machine learning. Sci Rep 10, 21541 (2020). https://doi.org/10.1038/s41598-020-78611-9","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fciwooooo%2Fhandwriting-classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fciwooooo%2Fhandwriting-classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fciwooooo%2Fhandwriting-classification/lists"}