Statistical Data Modeling and Machine Learning with Applications

The modeling and processing of empirical data is one of the main subjects and goals of statistics. Nowadays, with the development of computer science, the extraction of useful and often hidden information and patterns from data sets of different volumes and complex data sets in warehouses has been a...

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Bibliographic Details
Format:	eBook
Language:	English
Published:	Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:	artificial neural networks assessment banking brain-computer interface breast cancer subtyping CART ensembles and bagging categorical data citizen science classification classification and regression tree clustering CNN-LSTM architectures consensus models convexity cross-validation dam inflow prediction damped Newton data quality data-adaptive kernel functions deep forest Economics, Finance, Business and Management EEG motor imagery ensemble model feature selection Gower’s interpolation formula Gower’s metric hedonic prices housing hyper-parameter optimization image data Industry and industrial studies Information technology industries input predictor selection kernel clustering kernel density estimation long short-term memory machine learning mathematical competency Media, entertainment, information and communication industries METABRIC dataset mixed data multi-category classifier multi-omics data multidimensional scaling multivariate adaptive regression splines n/a non-linear optimization predictive models quantile regression real-time motion imagery recognition similarity stochastic gradient descent support vector machine wavelet transform
ISBN:	3036526927, 9783036526928, 9783036526935, 3036526935
Online Access:	Get full text
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