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logistic regression algorithm to identify candidate disease genes based on reliable protein-protein interaction network

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Science China(Information Sciences) 2021年第7期64卷 230-232页

作者： Xiujuan LEI Wenxiang ZHANG School of Computer Science Shaanxi Normal University

Dear editor,Genetic diseases have seriously threatened human health;however, identifying candidate disease genes is expected to contribute to understanding complex genetic diseases. Several machine learning algorithms... 详细信息

关键词： Disease genes logistic regression algorithm Multiple biological data Topological similarity of heterogeneous network Reconstructed PPI network

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Risk Prediction of Power Battery Based on logistic regression algorithm

Risk Prediction of Power Battery Based on Logistic Regressio...

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2021中国汽车工程学会年会暨展览会

作者： Li Yaohua Ren Chao Wang Xiaoyu Chen Guixin Liu Zikun Liu Dongmei School of Automobile Chang’an University

Today,when we advocate the development of new energy vehicles,the improvement of battery management system is an important factor in the development of electric ***,the estimation of the state of power batteries has become the key factor to ensure the safe driving of the *** research on the low residual charge of power battery mostly uses the charge and discharge data of single battery under ideal experimental conditions,which may not be able to adapt to the real complex and changeable driving conditions and separate from the real driving *** solve this problem,this work relies on the national big data alliance of new energy vehicles and uses the data-driven method to build a time-varying,battery voltage,battery current and other angles to reflect the current working status of the remaining power（SOC） of the power *** type of power battery used in this paper is lithium iron phosphate battery,and the alarm group and prediction group are *** data of the alarm group are the collected power battery data detected as low residual power（SOC）,and the data of the prediction group are the driving data of vehicles from May 9,2019 to November 5,*** logical regression algorithm is used to extract the battery characteristic information of low residual power,establish a model,and use the model to predict the data of the prediction group.

关键词： new energy vehicles power batteries low SOC logistic regression algorithm prediction

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Predicting Purchasing Behavior on E-Commerce Platforms: A regression Model Approach for Understanding User Features that Lead to Purchasing

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International Journal of Communications, Network and System Sciences 2024年第6期17卷 81-103页

作者： Abraham Jallah Balyemah Sonkarlay J. Y. Weamie Jiang Bin Karmue Vasco Jarnda Felix Jwakdak Joshua College of Computer Science and Engineering Hunan University Changsha China Department of Health Inspection and Quarantine Xiangya School of Public Health Central South University Changsha China

This research introduces a novel approach to improve and optimize the predictive capacity of consumer purchase behaviors on e-commerce platforms. This study presented an introduction to the fundamental concepts of the logistic regression algorithm. In addition, it analyzed user data obtained from an e-commerce platform. The original data were preprocessed, and a consumer purchase prediction model was developed for the e-commerce platform using the logistic regression method. The comparison study used the classic random forest approach, further enhanced by including the K-fold cross-validation method. Evaluation of the accuracy of the model’s classification was conducted using performance indicators that included the accuracy rate, the precision rate, the recall rate, and the F1 score. A visual examination determined the significance of the findings. The findings suggest that employing the logistic regression algorithm to forecast customer purchase behaviors on e-commerce platforms can improve the efficacy of the approach and yield more accurate predictions. This study serves as a valuable resource for improving the precision of forecasting customers’ purchase behaviors on e-commerce platforms. It has significant practical implications for optimizing the operational efficiency of e-commerce platforms.

关键词： E-Commerce Platform Purchasing Behavior Prediction logistic regression algorithm

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