Published Paper Details:

As machine learning technology advances quickly, more and more people pay attention to regression problems, which aid in extracting the pattern from vast amounts of data in order to produce a prediction impact. People now heavily rely on data prediction in their daily lives. The technique is currently widely employed in a variety of industries, including forecasting the weather, diagnosing illnesses, and the financial markets. As a result, one of the most active areas of research in the field of machine learning in recent years has been the study of machine learning algorithms in regression situations. This research mainly uses three popular machine learning algorithms: neural network, extreme learning machine, and support vector machine in order to more thoroughly explore the application effect of machine learning method in regression issue. Next, by contrasting the results of the benefits and drawbacks of each machine learning technique are examined by applying the single model and integrated model of these algorithms to regression situations. Here, we may choose any assignment that has to do with health, the weather, or an illness and compare it to the other difficulties to see which would provide the most accuracy.