
International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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Impact Factor: 9.24
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 7 Issue 3
May-June 2025
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DataCraft: A Web-Based Framework for Automated Machine Learning Analysis and Recommendation
Author(s) | Mr. Vishal Krishna Mahajan, Mr. Harsh Santosh Mahale, Mr. Pratik Babasaheb Mehetre, Mr. Rashmit Rajesh Mhatre, Mr. Jay Deepak Patil, Prof. Milind Vasantrao Kulkarni |
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Country | India |
Abstract | This paper presents a web-based framework for automated machine learning analysis and recommendation that streamlines the data science workflow. The system automatically performs data analysis, preprocessing, and model recommendation through an intuitive interface. The framework integrates dataset characterization, intelligent preprocessing suggestions, and context-aware model selection based on data characteristics and problem type. Results demonstrate the system's effectiveness in reducing the time and expertise required for preliminary data analysis while maintaining analytical rigor. The framework's web-based interface makes it accessible to both novice and experienced practitioners, contributing to the democratization of machine learning practices. |
Keywords | automated machine learning, data preprocessing, model recommendation, web-based framework |
Field | Computer > Artificial Intelligence / Simulation / Virtual Reality |
Published In | Volume 7, Issue 3, May-June 2025 |
Published On | 2025-05-31 |
DOI | https://doi.org/10.36948/ijfmr.2025.v07i03.45811 |
Short DOI | https://doi.org/g9mv2h |
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E-ISSN 2582-2160

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IJFMR DOI prefix is
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