Climate change has become one of the most severe and pressing world issues due to its destructive effects of environmental degradation. Climate change aggravates global warming and brings about potential risks for both human society and natural systems. The quantile regression being used to help with climate change is exceptionally new. The article scrutinizes the newest developments in this important research area and provides the future research directions.
Cox regression is the method for investigating the effect of several variables upon the time a specified event takes to happen. It is also known as the proportional hazards regression because it is all revolved around survival analysis. The Cox proportional hazards (CPH) model is the most frequently used approach for survival analysis in a wide variety of fields. This article summarizes current research, especially its applications in the area of diagnosis and treatment of coronavirus disease 2019 (COVID-19). Also, the pros and cons of competitive machine learning (ML) models for targeting the same object will be presented.
The Encyclopedia of Data Science and Machine Learning (EDSML) examines current, state-of-the-art research in the areas of data science, ML, data mining (DM), optimization, artificial intelligence (AI), statistics, and the interactions, linkages, and applications of knowledge-based business with information systems. It provides an international forum for practitioners, educators, and researchers to advance the knowledge and practice of all facets of BDML, emphasizing emerging theories, principles, models, processes, and applications to inspire and circulate cutting-edge findings into research, business, and communities. This encyclopedia contains a collection of 187 high-quality chapters, which were written by an international team of more than 370 experts representing leading scientists and talented young scholars from more than 46 countries and regions.
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