Table 1.

Summary of the main works in the literature.

Algorithms	Context/Objective	Work
Binary non-orthogonal Singular Value Decomposition (SVD)	Resource allocation optimization	[16]
XSOM (A modified SOM)	Handover management optimization	[18]
SOM	Anomaly detection	[19,20]
MGNG algorithm	Anomaly detection	[21]
Semi-supervised statistical-based algorithm	Sleeping cell detection	[22]
Rule-based system	Cell outage detection	[23]
Classification Tree	Diagnosis	[24]
Unsupervised techniques (SOM as the center-piece)	Diagnosis	[25]
SOM	Radio Frequencies (RF) conditions diagnosis	[26]
Random Forest, Deep Learning, Ridge Regression (Separated tests)	Transmission power prediction	[28]
Random Forest	Signal strength prediction	[29]
SOM	Cell pattern detection based on context information	[30]
SOM, K-Means	Cell pattern detection in 3G networks	[31]
SOM, K-Means	Radio access network analysis through behavioral patterns detection	[32]
SOM	Detection of daily traffic patterns	[33]
Naive Bayes, Holt-Winters	Classification of cells in terms of traffic	[34]
Unsupervised (Hierarchical clustering) and supervised (Random Forest) algorithms	Classification of traffic patterns by apps (Facebook, Twitter, Gmail, etc)	[35]
Improved Random Forest	Traffic pattern classification	[36]