A Survey of Machine Learning models for the wide Spectrum of Computational Biology
作者
Divya Ebenezer Nathaniel,Sonia F Panesar
出处
期刊:International journal of scientific research in computer science, engineering and information technology [Technoscience Academy] 日期:2019-02-02卷期号:: 604-611
标识
DOI:10.32628/cseit2063149
摘要
With the Advent of advancement in the field of Artificial Intelligence the computer is made more intelligent and can enable to think and make prediction accurately. The machine learning being a subfield of Artificial Intelligence is used in numerous research works. Different analysts feel that enormous data generated in field of biology have to be sorted in an intelligent way to yield best model. There are numerous kinds of Machine Learning Techniques like Unsupervised, Semi Supervised, Supervised, Reinforcement, and Evolutionary Learning and Deep Learning. These learning’s are used to classify huge data at a rapid pace. This paper discusses about the wide spectrum of Biology and the process of pre-processing data and the best suitable Machine learning model for each of them.