• K.V.VARAPRASAD
• ANUSHA.M
• S.FIROZ
• R.BHAVANA
• B.ANITHA

Wireless device network (WSN) is one in every of the foremost promising technologies for a few time period applications owing to its size, efficient and simply deployable nature. Expected to some external or internal factors, WSN could modification dynamically and thus it needs depreciative unneeded design of the network. The normal WSN approaches are expressly programmed that build the networks exhausting to reply dynamically to beat such issues, machine learning (ML) techniques are often applied to react consequently. CC is that the method of self-learning from the experiences and acts while not human intervention or re-program. The CC techniques was explained thoroughly. Some CC techniques in supervised learning i.e, K-NN, Deep learning, Support vector machines (SVM), call trees explained thoroughly.

Wireless device networks (WSN’s), Machine learning, K-NN, Deep learning, SVM, call trees

"A SURVEY ON MACHINE LEARNING TECHNIQUES FOR INTELLIGENT RADIO", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.180-185, March-2019, Available :http://www.jetir.org/papers/JETIRAK06033.pdf

"A SURVEY ON MACHINE LEARNING TECHNIQUES FOR INTELLIGENT RADIO", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp180-185, March-2019, Available at : http://www.jetir.org/papers/JETIRAK06033.pdf