Maintaining intellectual diversity in data science
نویسندگان
چکیده
منابع مشابه
Maintaining Diversity in Genetic Search
Genetic adaptive algorithms provide an efficient way to search large function spaces, and are increasingly being used in learning systems. One problem plaguing genetic learning algorithms is premature convergence, or convergence of the pool of active structures to a suboptimal point in the space being searched. An improvement to the standard genetic adaptive algorithm is presented which guarant...
متن کاملMaintaining science eminence.
COVER Partial view of the predictive map of high levels of arsenic in groundwater resources in China (blue, low probability; red, high probability; width, 600 kilometers; resolution, 1 square kilometer). Chronic arsenic poisoning from contaminated groundwater is a major health problem in many parts of China. An estimated 19.6 million people are potentially exposed to elevated arsenic concentrat...
متن کاملMaintaining Diversity in Agent-Based Evolutionary Computation
Niching techniques for evolutionary algorithms are aimed at maintaining the diversity through forming subpopulations (species) in multi-modal domains. Similar techniques may be applied to evolutionary multi-agent systems, which provide a decentralised model of evolution. In this paper a specific EMAS realisation is presented, in which the new species formation occurs as a result of co-evolution...
متن کاملMaintaining Genetic Diversity in Bacterial Evolutionary Algorithm
The Bacterial Evolutionary Algorithm (BEA) is a relatively new type of evolutionary algorithm and shows the typical phenomena of stochastic optimization methods. Two of these phenomena: premature convergence and low convergence speed near the optimum are often in connection with the low genetic diversity of the population. Variation of genetic diversity in the original BEA and in its three para...
متن کاملMaintaining Diversity in Population of Evolved Models
This paper deals with creation of models by means of evolutionary algorithms, particularly with maintaining diversity of population using niching methods. Niching algorithms are known for their ability to search for more optima simultaneously. This is done by splitting the population of models into separate species. Species protect promising but yet not fully developed models. Search for more o...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Data Science
سال: 2017
ISSN: 2451-8492,2451-8484
DOI: 10.3233/ds-170003