首页|Research from Boston University Broadens Understanding of Machine Learning (DREA MER: a computational framework to evaluate readiness of datasets for machine lea rning)
Research from Boston University Broadens Understanding of Machine Learning (DREA MER: a computational framework to evaluate readiness of datasets for machine lea rning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in artific ial intelligence. According to news reporting from Boston University by NewsRx j ournalists, research stated, "Machine learning (ML) has emerged as the predomina nt computational paradigm for analyzing large-scale datasets across diverse doma ins." Funders for this research include National Institutes of Health. The news correspondents obtained a quote from the research from Boston Universit y: "The assessment of dataset quality stands as a pivotal precursor to the succe ssful deployment of ML models. In this study, we introduce DREAMER (Data REAdine ss for MachinE learning Research), an algorithmic framework leveraging supervise d and unsupervised machine learning techniques to autonomously evaluate the suit ability of tabular datasets for ML model development. DREAMER is openly accessib le as a tool on GitHub and Docker, facilitating its adoption and further refinem ent within the research community.. The proposed model in this study was applied to three distinct tabular datasets, resulting in notable enhancements in their quality with respect to readiness for ML tasks, as assessed through established data quality metrics. Our findings demonstrate the efficacy of the framework in substantially augmenting the original dataset quality, achieved through the elim ination of extraneous features and rows. This refinement yielded improved accura cy across both supervised and unsupervised learning methodologies."
Boston UniversityCyborgsEmerging Tec hnologiesMachine Learning
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