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Titlebook: Advanced Communication and Intelligent Systems; Second International Rabindra Nath Shaw,Marcin Paprzycki,Ankush Ghosh Conference proceeding

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樓主: cerebral-cortex
11#
發(fā)表于 2025-3-23 10:19:23 | 只看該作者
Behind the Frontiers of the Realinal data set is randomly divided into 70% for training and 30% for testing. This segregation is fixed for all machine learning methods. This research shown that the best method for this case is RF, almost similar with SVM, and the prominent predictors to student retention are Sibling Active, Learning Process, Individual Approach and Observation.
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發(fā)表于 2025-3-23 16:10:39 | 只看該作者
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發(fā)表于 2025-3-23 20:10:51 | 只看該作者
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發(fā)表于 2025-3-23 22:24:58 | 只看該作者
Communications in Computer and Information Sciencehttp://image.papertrans.cn/a/image/145310.jpg
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發(fā)表于 2025-3-24 03:36:59 | 只看該作者
Conference proceedings 2023held in Warsaw, Poland,?during?June 16–17, 2023.The 22 full papers included in this book were carefully reviewed and?selected from?221?submissions. They were organized in topical sections as follows:?Wireless Communication, Artificial Intelligence and Machine Learning, Robotics & Automation, Data Science, IoT and Smart Applications.
16#
發(fā)表于 2025-3-24 06:52:20 | 只看該作者
Louis M. Imbeau,Thomas C. Eboutoulthcare industry, machine learning models were utilized in order to efficiently deliver conclusions regarding heart disease prediction. The adoption of methods derived from machine learning enables the reliable classification of individuals according to whether or not they are healthy. The framework
17#
發(fā)表于 2025-3-24 10:54:28 | 只看該作者
Constitutional Convulsions in Modern Greecehe needs and sustenance of a healthy population. The use of machine learning and AI tools have been employed in the health sector for a long time for different applications such as disease cure research, diagnosis, medication, etc. Similarly, these can be used for early identification of diseases wh
18#
發(fā)表于 2025-3-24 16:24:39 | 只看該作者
Constitutional Convulsions in Modern Greece cancer detection and diagnosis system based on artificial intelligence (AI) has the potential to increase early detection and improve treatment results. We have described the creation and assessment of an AI-based system in this paper that is intended for the identification of pancreatic cancer. A
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發(fā)表于 2025-3-24 22:31:05 | 只看該作者
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發(fā)表于 2025-3-25 01:45:04 | 只看該作者
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