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Entropy in Real-World Datasets and Its Impact on Machine Learning

The topic of the reprint is very important nowadays, because ever-evolving machine learning techniques make it possible to obtain better real-world data. Therefore, this reprint contains information related to real data in fields such as automatic sign language translation, bike-sharing travel chara...

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Gorde:
Formatua: Online
Hizkuntza:ingelesa
Argitaratua: MDPI - Multidisciplinary Digital Publishing Institute 2023
Gaiak:
machine learning
optical networks
imbalanced data
one-class classification
entropy measure
real-world data
preprocessing
decision table
classification
query set
decision tree
differential cryptanalysis
metaheuristics
symmetric block ciphers
memetic algorithms
DES
simulated annealing
COVID-19
vaccination
agent-based modelling
dynamic stochastic general equilibrium models
scenario analyses
validation of results
stock index forecasting
CEEMDAN
ADF
ARMA
LSTM
hybrid model
classification measure
quality of classification
quality measure
preference-driven classification
fast iterative filtering
parameter adaptive refined composite multiscale fluctuation-based dispersion entropy
rotating machinery
fault diagnosis
short-term demand prediction
bike-sharing
travel characteristics analysis
hybrid TCN-GRU model
distributed data
decision tables
information systems
decision trees
decision rules
tests
reducts
association rules
Pawlak conflict analysis model
independent data sources
coalitions
dispersed data
length
support
greedy heuristics
feature selection
rough sets
action units
automatic translation
sign language
entropy of real data
thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
thema EDItEUR::U Computing and Information Technology::UY Computer science
Sarrera elektronikoa:ONIX_20230714_9783036578484_57
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