Predictive and perspective analysis of cancer image data set using machine learning algorithms
Divya Chauhan, Kishori Lal Bansal · International Journal of Advanced Computer Research · 2020
Undoubtedly, machine learning is becoming a daily reality and need of the hour.It is an application of artificial intelligence that provides a system the ability to automatically learn as well as improve from the past experience.In fact, it deals with the learning process in which machine tends to learn on its own without being explicitly programmed [1].With time, machine learning has evolved by gaining new momentum as a consequence of learning from big data.Evidently it has brushed up the ability to automatically apply complex mathematical statistics on big data with greater efficiency and speed.Nowadays, the techniques of machine learning are ushering in mental and cognitive ability and can change the world if used deftly and calculative to harness its power. *Author for correspondenceBesides using the ability of machines to store and access more data than a person and adding machine learning on top of it to identify trends leads to arrive at a solution to previously untenable problems.One of the biggest applications of big data and machine learning is in the field of medical domain.Consequently, a health care organization that uses the techniques of machine learning and big data to treat patients see fewer mishaps or gets enough time to deal with them in advance.It is also helping medical organisations to tackle some of the most intractable problems by allowing the researcher to better understand the disease and predict the outburst of disease through the use of predictive models [2].There are many different kinds of machine learning algorithms to discover certain patterns in big data that leads to actionable insights.At the broader level, these machine learning algorithms can be divided into two groups based on the way they learn from the data to make predictions.These two groups are Research