The imbalanced data classification presents pervasive challenges in real-world data mining scenarios.To tackle these challenges, sampling techniques have emerged as effective approaches.However, the prevailing technique, SMOTE (Synthetic Minority Over-sampling Technique), and its derivatives make the assumption that each minority class observation

The analysis of immigration policy on a local space is an important contribution by emphasis on the need for local governments in the United States to redefine its role in the Interior state, which involves thinking about re-emerging activism of local governments thta has promoted the generation of new practices and Finishing Touches immigration la

Abstract In this paper, we propose the quantum semi-supervised generative adversarial network (qSGAN).The system is composed of a quantum generator and a Olive Oil classical discriminator/classifier (D/C).The goal is to train both the generator and the D/C, so that the latter may get a high classification accuracy for a given dataset.Hence the qSGA

Pitch-class distributions are of central relevance in music information retrieval, computational musicology and various other fields, such as music perception and cognition.However, despite their structure being closely related to the cognitively and musically relevant properties of a piece, many existing approaches treat Deck Shoes pitch-class dis