A Conceptual review on different data clustering algorithms and a proposed insight into their applicability in the context of Covid-19

AI has paved the way which has enabled us to produce machines resembling human intelligence. Because of AI it is now possible that machines learn from experience and perform real thinking and tasks. For which this has been possible is named Machine Learning which has various sections under it. There are four different types of this area – Supervised Learning, Unsupervised Learning, Semi-supervised Learning and Reinforcement Learning. Machine Learning basically focuses on the learning of computers and performing tasks by themselves. Unsupervised learning is the one where no labelled input is there so, machine only identifies patterns in data and separate them into different clusters. Data clustering algorithm is an unsupervised type of machine learning where clusters get created from scattered data of any shape from unlabelled input. In this paper, some renowned data clustering algorithms to date and their applications will be analysed and discussed comparatively. And also, will provide an insight into helping them to be used in applications on the research field of Covid-19. Studying and analysing the Data Clustering Algorithms and their applications and utilising that to help in research field of Contagious diseases like, Covid-19 has been discussed and proposed in our research. Literature survey has been conducted to carry out this paper work. Google web search engine and Google Scholar search engine have been used to conduct research. Comparatively studying the Data Clustering Algorithms and their applications gave us insight that these can be employed into the research field of Covid-19 analysis. As have been discussed in the proposed hypothesises, this paper can widely be operated in the field of Biotech or Medicine, in genome research, or also, getting statistical data like infection regions, infection patterns, infected population etc. can be covered which will finally help in mitigating the impact of this disease, Covid-19. This is our expectation that with this review of data clustering algorithms as a future work, the hypothesises proposed here shall be researched more into experiments which will help measure the impact and effectiveness of Covid-19 like contagious diseases.