Data Science: Measuring Uncertainties

• Other Authors: De Bragança Pereira, Carlos Alberto (Editor), Polpo, Adriano (Editor), Rodrigues, Agatha (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Subjects: Research & information: general; Mathematics & science; model-based clustering; mixture model; EM algorithm; integrated approach; density estimation; distribution free; non-parametric statistical test; decoy distributions; size invariance; scaled quantile residual; maximum entropy method; scoring function; outlier detection; overfitting detection; time series of counts; Bayesian hierarchical modeling; Bayesian nonparametrics; Pitman-Yor process; prior sensitivity; clustering; Bayesian forecasting; singular spectrum analysis; robust singular spectrum analysis; time series forecasting; mutual investment funds; relative entropy; cross-entropy; uncertain reasoning; inductive logic; confirmation measure; semantic information; medical test; raven paradox; Markov random fields; probabilistic graphical models; multilayer networks; objective Bayesian inference; intrinsic prior; variational inference; binary probit regression; mean-field approximation; multi-attribute emergency decision-making; intuitionistic fuzzy cross-entropy; grey correlation analysis; earthquake shelters; attribute weights; time series; Bayesian inference; hypothesis testing; unit root; cointegration; Rényi entropy; discrete Kalman filter; continuous Kalman filter; algebraic Riccati equation; nonlinear differential Riccati equation; cloud model; fuzzy time series; stock trend; Heikin-Ashi candlestick; water resources; channel; mathematical entropy model; bank profile shape; gene expression programming (GEP); entropy; genetic programming; artificial intelligence; data science; big data; n/a
• Online Access: DOAB: download the publication; DOAB: description of the publication

With the increase in data processing and storage capacity, a large amount of data is available. Data without analysis does not have much value. Thus, the demand for data analysis is increasing daily, and the consequence is the appearance of a large number of jobs and published articles. Data science...