“…For example, predict the location of a mobile node using an algorithm that is trained on signal propagation characteristics (inputs) at known locations (outputs). Various challenges in wireless networks have been addressed using supervised learning such as: medium access control [ 29 , 42 , 43 , 44 ], routing [ 45 ], link quality estimation [ 46 , 47 ], node clustering in WSN [ 48 ], localization [ 49 , 50 , 51 ], adding reasoning capabilities for cognitive radios [ 36 , 37 , 52 , 53 , 54 , 55 , 56 ], etc . Supervised learning has also been extensively applied to different types of wireless networks application such as: human activity recognition [ 21 , 39 , 57 , 58 , 59 , 60 ], event detection [ 61 , 62 , 63 , 64 , 65 ], electricity load monitoring [ 66 , 67 ], security [ 68 , 69 , 70 ], etc .…”