Class (philosophy)

About: Class (philosophy) is a research topic. Over the lifetime, 821 publications have been published within this topic receiving 28000 citations.

Neural Network-Based Undersampling Techniques

Abstract: Machine learning models have gained popularity nowadays for their potential to solve real-life issues when trained on pertinent data. In many cases, the real-life data are class imbalanced and hence the corresponding machine learning models trained on the data tend to perform poorly on metrics like precision, recall, AUC, F1, and G-mean score. Since class imbalance issue poses serious challenges to the performance of trained models, a multitude of research works have addressed this issue. Two common data-based sampling techniques have mostly been proposed-undersampling the data of the majority class and oversampling the data of the minority class. In this article, we focus on the former approach. We propose two novel algorithms that employ neural network-based approaches to remove majority samples that are found to reside in the vicinity of the minority samples, thereby undersampling the former to remove (or alleviate) the imbalance issue. We delineate the proposed algorithms and then test the proposed algorithms on some publicly available imbalanced datasets. We then compare the performance of our proposed algorithms to other popular undersampling algorithms. Finally, we conclude that our proposed algorithms outperform most of the existing undersampling approaches on most performance metrics.

The Jordan property for local fundamental groups

Abstract: We show the Jordan property for regional fundamental groups of klt singularities of fixed dimension. Furthermore, we prove the existence of effective simultaneous index one covers for $n$-dimensional klt singularities. We give an application to the study of local class groups of klt singularities.

How teacher behaviour shapes foreign language learners’ enjoyment, anxiety and attitudes/motivation: A mixed modelling longitudinal investigation

Abstract: The current study investigates how foreign language enjoyment (FLE), foreign language classroom anxiety (FLCA) and attitude/motivation (AM) of 360 learners of English, German, French and Spanish in a Kuwaiti university was shaped over the course of one semester by three teacher behaviours: frequency of using the foreign language (FL) in class, predictability and frequency of joking. Linear mixed modelling revealed a positive relationship between the three teacher behaviours and FLE as well as AM, but no significant relationship emerged with FLCA. Multiple comparison analyses showed that levels of FLE dropped significantly among students whose teacher joked very infrequently and infrequently. It thus seems that the absence of teacher jokes had a delayed cumulative effect on FLE. No interaction effects were found with time for FLCA and for AM. We conclude that teacher behaviours affect both AM and FLE, and that frequency of joking actually shapes FLE over time.