A comparative approach of unsupervised machine learning techniques for LTE network parameter clustering.
Nicola PasquinoStefania ZinnoFederica CotugnoSofia PetrocelliPublished in: I2MTC (2020)
Keyphrases
- unsupervised learning
- clustering algorithm
- clustering method
- network parameters
- unsupervised classification
- unsupervised feature selection
- cellular networks
- k means
- peer to peer
- computer networks
- unsupervised manner
- unsupervised clustering
- parameter values
- network model
- network traffic
- machine learning
- information bottleneck
- supervised classification
- hierarchical clustering
- communication networks
- neural network
- data clustering
- complex networks
- self organizing maps
- wireless networks
- machine learning algorithms
- spectral clustering
- machine learning approaches
- mobile networks
- energy saving
- network structure
- anomaly detection
- cluster validation
- minimum message length