Statistical Data Modeling and Machine Learning with Applications

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:
Information technology industries
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
EEG motor imagery
ensemble model
feature selection
Gower's interpolation formula
Gower's metric
hedonic prices
housing
hyper-parameter optimization
image data
input predictor selection
kernel clustering
kernel density estimation
long short-term memory
machine learning
mathematical competency
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
Online Access:Open Access: DOAB: description of the publication
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