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您的检索式：作者名="Bryan Keane"
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| 1 | 2005年亚洲娱乐焦点显示文摘2005年的亚洲娱乐圈里,最让大家眼前一亮的是哪颗星星呢?小编很赞同美国媒体的选择——韩星Rain。 单眼皮帅哥Rain在不够一年的时间里就席卷亚洲,俘虏了无数女影迷的心,连我这个老大不小的、看腻了中 外美男的娱编也忍不住看着他的相片傻笑,还不时臭美地照照镜子,感叹自己长得还挺像《浪漫满屋》里让 Rain爱得死去活来的宋慧乔(清醒时才发现只是后脑勺像而已)。什么?你对韩流不感冒? | Donald Macintyre Keane Shum Bryan Walsh 小狐 | 2005 | 疯狂英语(阅读版)2005，0，12： | 0 |
| 2 | Credit Card Fraud Detection on Original European Credit Card Holder Dataset Using Ensemble Machine Learning Technique显示文摘The proliferation of digital payment methods facilitated by various online platforms and applications has led to a surge in financial fraud,particularly in credit card transactions.Advanced technologies such as machine learning have been widely employed to enhance the early detection and prevention of losses arising frompotentially fraudulent activities.However,a prevalent approach in existing literature involves the use of extensive data sampling and feature selection algorithms as a precursor to subsequent investigations.While sampling techniques can significantly reduce computational time,the resulting dataset relies on generated data and the accuracy of the pre-processing machine learning models employed.Such datasets often lack true representativeness of realworld data,potentially introducing secondary issues that affect the precision of the results.For instance,undersampling may result in the loss of critical information,while over-sampling can lead to overfitting machine learning models.In this paper,we proposed a classification study of credit card fraud using fundamental machine learning models without the application of any sampling techniques on all the features present in the original dataset.The results indicate that Support Vector Machine(SVM)consistently achieves classification performance exceeding 90%across various evaluation metrics.This discovery serves as a valuable reference for future research,encouraging comparative studies on original dataset without the reliance on sampling techniques.Furthermore,we explore hybrid machine learning techniques,such as ensemble learning constructed based on SVM,K-Nearest Neighbor(KNN)and decision tree,highlighting their potential advancements in the field.The study demonstrates that the proposed machine learning models yield promising results,suggesting that pre-processing the dataset with sampling algorithm or additional machine learning technique may not always be necessary.This research contributes to the field of credit card fraud detection by emphasizing the potential of employing machine learning models directly on original datasets,thereby simplifying the workflow and potentially improving the accuracy and efficiency of fraud detection systems. | Yih Bing Chu Zhi Min Lim Bryan Keane Ping Hao Kong Ahmed Rafat Elkilany Osama Hisham Abusetta | 2023 | Journal of Cyber Security2023，5，1： | 0 |
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