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Titlebook: Computational Intelligence in Data Mining; Proceedings of the I Himansu Sekhar Behera,Janmenjoy Nayak,Danilo Pelus Conference proceedings 2

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樓主: microbe
11#
發(fā)表于 2025-3-23 11:24:58 | 只看該作者
Rating Prediction of Tourist Destinations Based on Supervised Machine Learning Algorithms,ia corpus based on different places around?the world. Intelligent predictions?about the possible popularity of a tourist location will be very helpful for personal and commercial purposes. To?predict the demand for the site, rating score on a range of 1–5 is a proper measure of the popularity of a p
12#
發(fā)表于 2025-3-23 14:19:41 | 只看該作者
13#
發(fā)表于 2025-3-23 19:02:53 | 只看該作者
Prediction of Arteriovenous Nicking for Hypertensive Retinopathy Using Deep Learning,ng one of the causes of hypertensive blood pressure, it is needed to be diagnosed at an early stage. This paper explains a method devised using deep learning to classify arteriovenous nicking using the retinal images of the patient. The dataset provided by the Structured Analysis of the Retina proje
14#
發(fā)表于 2025-3-24 00:12:42 | 只看該作者
15#
發(fā)表于 2025-3-24 04:53:33 | 只看該作者
,Trendingtags—Classification & Prediction of Hashtag Popularity Using Twitter Features in Machine Lerending in the near future is of significant importance for taking proper decisions in news media, marketing and social media advertising. This research work is aimed at predicting the popularity and tagging the hash tags using machine learning algorithms. It categorizes the popularity under five cl
16#
發(fā)表于 2025-3-24 08:23:11 | 只看該作者
17#
發(fā)表于 2025-3-24 11:02:24 | 只看該作者
18#
發(fā)表于 2025-3-24 15:24:44 | 只看該作者
19#
發(fā)表于 2025-3-24 21:26:10 | 只看該作者
20#
發(fā)表于 2025-3-25 02:59:03 | 只看該作者
Environmental Games and Queue Models depict the improvements of Random Forest in terms of computational time and memory without affecting the efficiency of the traditional Random Forest. Experimental results show that the proposed RRF outperforms with others in terms of memory utilization and computation time.
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