Statistical Data Modeling and Machine Learning with Applications

• Otros Autores: Gocheva-Ilieva, Snezhana (Editor)
• Formato: Electrónico Capítulo de libro
• Lenguaje: inglés
• Publicado: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Materias: Information technology industries; mathematical competency; assessment; machine learning; classification and regression tree; CART ensembles and bagging; ensemble model; multivariate adaptive regression splines; cross-validation; dam inflow prediction; long short-term memory; wavelet transform; input predictor selection; hyper-parameter optimization; brain-computer interface; EEG motor imagery; CNN-LSTM architectures; real-time motion imagery recognition; artificial neural networks; banking; hedonic prices; housing; quantile regression; data quality; citizen science; consensus models; clustering; Gower's interpolation formula; Gower's metric; mixed data; multidimensional scaling; classification; data-adaptive kernel functions; image data; multi-category classifier; predictive models; support vector machine; stochastic gradient descent; damped Newton; convexity; METABRIC dataset; breast cancer subtyping; deep forest; multi-omics data; categorical data; similarity; feature selection; kernel density estimation; non-linear optimization; kernel clustering; n/a
• Acceso en línea: DOAB: download the publication; DOAB: description of the publication

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...