Class (philosophy)

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

Research on prediction of multi-class theft crimes by an optimized decomposition and fusion method based on XGBoost

Abstract: The number of theft cases is much higher than that of other criminal cases, which frequently occurs in daily life and is seriously destructive to social order. Studying the law of theft cases has a positive impact on social governance and optimizing police deployment. Therefore, based on the data of theft cases in H city, this study proposes an optimized decomposition and fusion method based on XGBoost, and establishes two multi-classification prediction models, such as OVR-XGBoost and OVO-XGBoost. As the theft data is a datasets with unbalanced class distribution, this paper uses SMOTENN algorithm to process it into a datasets with balanced distribution, which effectively improves the effect of the model. Experiments show that the prediction accuracy of OVR-XGBoost and OVO-XGBoost models is higher than that of baseline XGBoost models. For categories with few samples, the classification effect of OVO-XGBoost is better than that of baseline XGBoost and OVO-XGBoost models. Compared with baseline XGBoost model, the average overall classification accuracy of OVO-XGBoost model is improved by more than 7%, and the MacroR accuracy is also improved by more than 15%. The model proposed in this study has a good effect on the classification and prediction of theft types, and is of great significance for the prevention of theft cases.

Application of Machine Learning and Internet of Things Techniques in Evaluation of English Teaching Effect in Colleges

Abstract: College English classroom teaching evaluation is one of the key issues discussed by all schools at present. First of all, teachers and students are highly concerned about English learning in the compulsory course of English examination, but there are also many problems. The distance network teaching with computer technology as the main body develops rapidly, a large number of video and audio teaching resources network through the network transmission to present in front of learners, through the network transmission of video and audio aided, expand the audience of network teaching, is conducive to the realization of digitalization, information, lifelong, new education goals. Firstly, this article summarizes the problems of poor effect, uneven performance, and mismatch between evaluation and teaching in college English at present. Then, based on the previous works, the author designed a machine learning-based Internet of things technology and verifies its feasibility. The data of teaching experiments show that the writing performance of the students in the lower section of the experimental class is better than that of the students in the middle and high sections. Among them, significant progresses have been made in grammar, length, expression, and structure, which has optimized students' preclass preview efficiency, autonomous learning motivation, quality of homework completion, and afterclass reflection behavior. Finally, the author summarized the shortcomings of this research and puts forward the prospect of relevant research, in order to provide reference value for the national college English blended teaching and promotes the efficient implementation and vigorous development of college English teaching. In the future, the evaluation index system under the pressure of performance can be further studied.

Measure data elliptic problems with generalized Orlicz growth.

Abstract: We study nonlinear measure data elliptic problems involving the operator exposing generalized Orlicz growth. Our framework embraces reflexive Orlicz spaces, as well as natural variants of variable exponent and double-phase spaces. Approximable and renormalized solutions are proven to exist and coincide for arbitrary measure datum and to be unique when the datum is diffuse with respect to a relevant nonstandard capacity. For justifying that the class of measures is natural, a capacitary characterization of diffuse measures is provided.

MXenes as Emerging Class of Two-Dimensional Materials for Advanced Energy Storage Devices

Abstract: A class of two-dimensional (2D) transition metal nitrides and carbides (MXenes) has emerged as a promising paradigm. Their unique architecture such as controllable interfacial chemistry, high electronic conductivity, tunable layered...