{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-topological-data-analysis-based","title":"A topological data analysis based classification method for multiple measurements","arxiv_id":"1904.02971","date":"2019-04-05","proceeding":null,"authors":["Henri Riihimäki","Wojciech Chachólski","Jakob Theorell","Jan Hillert","Ryan Ramanujam"],"abstract":"Machine learning models for repeated measurements are limited. Using\ntopological data analysis (TDA), we present a classifier for repeated\nmeasurements which samples from the data space and builds a network graph based\non the data topology. When applying this to two case studies, accuracy exceeds\nalternative models with additional benefits such as reporting data subsets with\nhigh purity along with feature values. For 300 examples of 3 tree species, the\naccuracy reached 80% after 30 datapoints, which was improved to 90% after\nincreased sampling to 400 datapoints. Using data from 100 examples of each of 6\npoint processes, the classifier achieved 96.8% accuracy. In both datasets, the\nTDA classifier outperformed an alternative model. This algorithm and software\ncan be beneficial for repeated measurement data common in biological sciences,\nas both an accurate classifier and a feature selection tool.","url_abs":"http://arxiv.org/abs/1904.02971v1","url_pdf":"http://arxiv.org/pdf/1904.02971v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-topological-data-analysis-based","repo_url":"https://github.com/ryaram1/mmTDA","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"point-processes","task_name":"Point Processes"},{"task_slug":"topological-data-analysis","task_name":"Topological Data Analysis"},{"task_slug":"feature-selection","task_name":"feature selection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}