In several applications of text classification, training document labels are provided by human evaluators, and therefore, gathering sufficient data for model creation is time consuming and costly.The labeling time and effort may be reduced by active learning, in which classification models are created based on relatively small training sets, which
t-SNE (t-distributed Stochastic Neighbor Embedding) is known to be one of the very powerful tools for dimensionality reduction and data visualization.By adopting the student’s t-distribution in the original SNE (Stochastic Neighbor Embedding), t-SNE achieves faster and more stable learning.However, t-SNE still poses computational complexity
With the continuous development of automation and information technology, large amounts of safety data are produced in the processes of coal production.Most enterprises simply focus on statistics and do not conduct systematic big data analyses.Therefore, it is necessary to study IMMEDIATE RELEF the theory of coal mine safety while using big data sy
Objective: The objective of the article is to conceptualize and systematize the most relevant dimensions and issues of migrant entrepreneurship based on the literature review.Research Design & Methods: In the article, we applied a narrative literature review.We identified.relevant publications by indicating keywords that allowed for the selection o
Background.Rhynchophorus palmarum is the main insect pest in Cocos nucifera orchards in the Pacific Centre of Mexico.The mass capture of adults is the strategy for control of this pest promoted by integrated pest management programs.It is essential to find an economic and efficient trap for farmers.Objective.The present study aimed to determine the