机器学习课程设计 针对热点新闻的DBSCAN聚类模型识别预测报告

上传者: m0_55753222 | 上传时间: 2024-06-26 13:39:29 | 文件大小: 24.86MB | 文件类型: ZIP
针对某一具体问题(例如,可以来源于当前时事和大学学习、生活、竞赛等紧密相关的topic(如天气、生态环境、各类竞赛等)),采用机器学习算法实现其分类、识别、预测等。 如:基于SVM的图像分类或回归,通过特征参数提取,训练得到SVM模型,再利用该模型对图像进行分类;或用深度学习模型来自动提取特征+预测等等。 1. 题目(选个有意思、吸引眼球、言简意赅的题目很重要); 2. 中英文摘要和关键词; 3. 背景(问题描述,应用意义,研究现状,存在挑战,解决方案等); 4. 原理方法(对所用的机器学习算法进行原理介绍,图,文,公式,重点是模型的输入输出参数); 5. 解决方案(对所解决问题的方案进行详细描述,重点解决方案中的模型,图,文,公式,模型参数训练,特征提取,学习算法等); 6. 实验结果分析(给出所实现的结果,图文描述(含该模型的过拟合分析),若有对比结果可加分); 7. 结论(描述本文所解决的问题,与传统方法的优势,还存在哪些待解决的问题);

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