Recent hybrid machine learning algorithm applications: a review
As a result of the advancement of machine languages and algorithms, as well as the expansion of the sectors in which they can be employed in the present day, there has been an improvement in both the precision of forecasts and the speed with which optimal solutions may be found in all aspects of life.
Based on an analysis of 16 research articles published in respected journals this year, and an investigation of what makes this research special, this study will analyze the hybrid machine algorithms that will be most essential in 2022, as well as the many fields in which they will be used. The goal of this research is to look into the hybrid machine algorithms that will be most relevant in this field. We attempted to identify between these methods by using three criteria: the type of hybrid algorithm, the data set used, and the type of data.