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Extreme Learning Machine for Interval-Valued Data
2014Extreme learning machine (ELM) is a fast learning algorithm for single hidden layer feed-forward neural networks, but it only can deal with the data sets with numerical attributes. Interval-valued data is considered as a direct attempt to extend precise real-valued data to imprecise scenarios.
Shixin Zhao, Xizhao Wang
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An overview of real‐world data sources for oncology and considerations for research
Ca-A Cancer Journal for Clinicians, 2022Lynne Penberthy +2 more
exaly
Dependencies in Bivariate Interval-Valued Symbolic Data
2004This paper looks at measures of dependence for symbolic intervalvalued data. A method is given to calculate an empirical copula for a bivariate interval-valued variable. This copula is then used to determine an empirical formula for calculating Spearman’s rho for such data. The methodology is illustrated from a set of hematocrit-hemoglobin data and the
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Innovations in research and clinical care using patient‐generated health data
Ca-A Cancer Journal for Clinicians, 2020H S L Jim +2 more
exaly
Compositional Linear Regression on Interval-valued Data
2021 IEEE Symposium Series on Computational Intelligence (SSCI), 2021Direnc Pekaslan, Christian Wagner
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Control charting with interval-valued data
Quality EngineeringStefan H. Steiner, William H. Woodall
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