{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9652716","patent":{"patent_number":"US-9652716","title":"Extracting interpretable features for classification of multivariate time series from physical systems","assignee":null,"inventors":[],"filing_date":"2014-10-29T00:00:00.000Z","publication_date":"2017-05-16T00:00:00.000Z","cpc_codes":["G06N","G06N"],"num_claims":14,"abstract":"A method and system are provided. The method includes extracting shapelets from each of a plurality of time series dimensions of multi-dimensional time series data. The method further includes building a plurality of decision-tree classifiers, one for each time series dimension, responsive to the shapelets extracted therefrom. The method also includes generating a pairwise similarity matrix between respective different ones of the plurality of time series dimensions using the shapelets as intermediaries for determining similarity. The method additionally includes applying a feature selection technique to the matrix to determine respective feature weights for each of shapelet features of the shapelets and respective classifier weights for each of the decision-tree classifiers that uses the shapelet features. The method further includes combining decisions issued from the decision-tree classifiers to generate a final verdict of classification for a time series dimension responsive to the respective feature weights and the respective classifier weights."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Extracting interpretable features for classification of multivariate time series from physical systems","description":"A method and system are provided. The method includes extracting shapelets from each of a plurality of time series dimensions of multi-dimensional time series data. The method further includes buildin","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9652716","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-9652716","citation_suggestion":"Patentable. \"Extracting interpretable features for classification of multivariate time series from physical systems\" (US-9652716). https://patentable.app/patents/US-9652716","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9652716","json":"https://patentable.app/api/llm-context/US-9652716","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-06-06T05:39:50.444Z"}