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- W4384389706 abstract "Curve fitting is a fundamental task in data analysis, allowing researchers to uncover underlying patterns and relationships in their datasets. In this paper, we introduce CurvPy, a powerful data analysis tool designed to streamline the curve-fitting process. CurvPy offers three main functionalities: DataSleuth, FuncPlot, and OptiFit. DataSleuth analyses input data in CSV format and provides a best-guess estimate of the underlying mathematical function. FuncPlot enables users to visually inspect the fit between the function and the data by generating graphs. OptiFit harnesses the power of optimal parameters, allowing effortless optimisation of equation parameters for precise and efficient data modelling. CurvPy is built using Flask, pandas, numpy, matplotlib, scipy, and scikit-learn, providing a user-friendly interface and efficient computational capabilities. By integrating these tools, CurvPy empowers researchers to gain insights from their data and will help to make decisions. Evaluation demonstrates the effectiveness and efficiency of CurvPy in diverse curve-fitting scenarios. The availability of CurvPy as an open-source tool further encourages collaboration and expands its potential applications in various domains. Overall, CurvPy offers a comprehensive solution for curve-fitting tasks and holds great promise for advancing data analysis techniques." @default.
- W4384389706 created "2023-07-15" @default.
- W4384389706 creator A5092474546 @default.
- W4384389706 date "2023-06-24" @default.
- W4384389706 modified "2023-09-25" @default.
- W4384389706 title "Curve Fitting Simplified: Exploring the Intuitive Features of CurvPy" @default.
- W4384389706 doi "https://doi.org/10.48550/arxiv.2307.06377" @default.
- W4384389706 hasPublicationYear "2023" @default.
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