使用Web应用程序预测选定数据集的最优值的模型的开发

Iliyas Abduali, Aldiyar Ibragimov
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引用次数: 0

摘要

数据分析工具、数据可视化以及预测最优值或获得预期结果的能力对人们来说变得越来越必要。这种需求既适用于专业分析师、科学家、每天与数据打交道的专家,也适用于那些没有如此深厚的数据知识的人。在这方面,我们研究和分析了帮助人们在处理数据时解决新出现的问题的作品。因此,我们已经确定需要创建一个平台,可以提供必要的工具和算法来解决出现的问题。因此,我们基于Streamlit库开发了一个原型web平台,并根据接收到的数据开发了一个模型来预测最优值。建立模型需要我们研究和分析合适的科学方法。在开发的平台中,用户可以上传数据,以自己需要的方式将数据可视化,可以选择机器学习方法,并使用我们的算法接收预测以获得最优值。在工作的最后,我们对所构建的模型进行了测试,计算了模型的精度,得到了满意的结果。因此,我们开发了一个最优价值分析和预测模型,目前最适合预测房地产价格。我们在已开发的web平台上使用了这个模型,在那里我们使用一个可理解的、用户友好的界面,并提供处理数据所需的基本工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of a Model for Predicting the Optimal Value for Selected Dataset Using a Web Application
Data analysis tools, data visualization, and the ability to predict the optimal value or obtain the desired result are becoming more and more necessary for people. This need arises both for professional analysts, scientists, specialists who work with data daily, and for people who do not have such deep knowledge to work with data. In this regard, we studied and analyzed works that helped people in solving emerging problems when working with data. Thus, we have identified the need to create a platform that could provide the necessary tools and algorithms to resolve the issues that have arisen. Therefore, we developed a prototype web platform based on the Streamlit library and developed a model to predict the optimal value based on the data received. Building the model required us to study and analyze the appropriate scientific methods. In the developed platform, the user can upload data, visualize them in the way they need, can choose machine learning methods, and receive with our algorithm a forecast to obtain the optimal value. At the end of our work, we tested the constructed model to calculate the accuracy, which showed satisfactory results. As a result, we have developed an optimal value analysis and prediction model, which currently works best for predicting real estate prices. We used this model on the developed web platform, where we use an understandable, user-friendly interface and provide the fundamental tools necessary to work with data.
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