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Titlebook: Artificial Intelligence: Theory and Applications; Proceedings of AITA Harish Sharma,Antorweep Chakravorty,Rajani Kumari Conference proceed

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發(fā)表于 2025-3-28 14:36:37 | 只看該作者
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發(fā)表于 2025-3-29 00:38:13 | 只看該作者
Co-GA: A Bio-inspired Semi-supervised Framework for Fake News Detection on Scarcely Labeled Data,ake news detection methodology. One of the key challenges faced by researchers is the lack of sufficient labeled data making semi-supervised learning increasingly important for social media data. Non-latent content features differ in fake and real news but at the same time suffer from the high-dimen
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發(fā)表于 2025-3-29 03:56:03 | 只看該作者
,Kernel Methods for?Conformal Prediction to?Detect Botnets,s a critical task in cybersecurity, and machine learning techniques have been widely employed for this purpose. In this paper, we present a novel approach for botnet detection based on kernel methods and conformal prediction. Our method leverages the power of kernel functions to capture complex patt
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發(fā)表于 2025-3-29 07:19:41 | 只看該作者
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發(fā)表于 2025-3-29 21:39:26 | 只看該作者
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發(fā)表于 2025-3-30 02:03:12 | 只看該作者
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發(fā)表于 2025-3-30 04:11:15 | 只看該作者
Predicting of Credit Risk Using Machine Learning Algorithms, more rigid forecasting models with strong mapping abilities, credit risk prediction has become challenging for the banking industry. Therefore, this paper attempts to predict commercial banks’ credit risk (CR) by using various machine learning algorithms. Machine learning algorithms, namely linear
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