回归分析和可视化抽搐数据集

2022 3rd International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT) Pub Date : 2022-11-11 DOI:10.1109/ICICT55121.2022.10064568

Insha Khan, Riya Kumari, N. Sharma, M. Mangla, Inderdeep Kaur

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引用次数: 1

摘要

本文对Twitch数据集进行了研究，以确定和揭示数据集的各个方面和属性之间的关系。Twitch是用于视频游戏直播的在线平台。作者在分析中使用的模型是逻辑回归，Naïve贝叶斯，k近邻和决策树。正如作者所证明的那样，k近邻和逻辑回归的准确率分别为97.7%和97.4%，优于其他模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Regression Analysis & Visualization of Twitch Dataset

This paper examines Twitch dataset in order to determine and unveil various aspects and relationship among attributes of dataset. Twitch is an online platform used for video game live streaming. The models used by authors in their analysis are Logistic regression, Naïve Bayes, K-Nearest Neighbour and Decision tree. As demonstrated by the authors, K-Nearest Neighbour and logistic regressions outperform other model by yielding an accuracy of 97.7% and 97.4 %.

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来源期刊

2022 3rd International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT)

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