At the same time, most applications of social network analysis to non-human animals have been at a descriptive level, using various computational methods to quantify features of social structure and individuals' position in it. These methods, combined with increasingly detailed data 'reality mining'...
State If this is not possible. Describe the differences among classification, clustering, and association rule data mining. Is the following list of data quantitative or qualitative? (5, 6.5, 1, 0) Define and give an example of Quantitative variables. What are t...
One problem with arguments of this kind is that they weigh up only basic economic and technological factors and fail to consider the hidden environmental costs of things like oil spills, air pollution, land destruction from coal mining, or climate change—and especially the future costs, which ar...
This has motivated the organization of the ESANN 2015 Special Session in Advances in Learning Analytics and Educational Data Mining. Here, a review of research and practice in LA and EDM is presented accompanied by the most central methods, bene- ts, and challenges of the eld. Additionally, ...
Chinese enterprises even invest in advanced countries such as Australia to achieve the efficient mining sector in order to guarantee the demand of the energy in the home market [43,44]. Thus: Hypothesis 5 (H5). Chinese OFDI along BRI countries is correlated positively with host country ...
Ribeiro, M.T.; Singh, S.; Guestrin, C. “Why Should I Trust You?”: Explaining the Predictions of Any Classifier. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA, 13–17 August 2016; Association for Computing ...