Solutions to Critical issues on Big Data Using Machine Learning Techniques - S. Umadevi , T.Chandrakala , B.Bavani , S.Leena Nesamani , TM.Ezhilmathi (International Journal of Advanced Science and Technology, 2020)
Nowadays big data have been used tremendously in all areas of computer engineering. The main advantage of big data is that the user is able to analyze huge data and can refer different possible opportunities. Initially traditional machine learning methods like supervised learning, unsupervised learning and reinforcement learning are used. But the traditional techniques are not able to cope up with massive amount of data ,also in traditional technique the data collected are stored in a centralized unit which will be very difficult as the amount of data grew bigger. To overcome this advanced machine learning techniques like Representation learning, Deep Learning, Distributed and parallel learning, Transfer learning and Active Learning are proposed. These learning techniques also have certain critical issues like huge scale data learning, Different data categories learning. High speed continuous data learning and mining valuable data learning. Various problems and their solutions to these issues are discussed below