首页|Research on Artificial Intelligence Published by Researchers at Lund University (Xputer: bridging data gaps with NMF, XGBoost, and a streamlined GUI experience)
Research on Artificial Intelligence Published by Researchers at Lund University (Xputer: bridging data gaps with NMF, XGBoost, and a streamlined GUI experience)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in artificial intelligence. According to news reporting from Lund, Sweden, by NewsR x journalists, research stated, “The rapid proliferation of data across diverse fields has accentuated the importance of accurate imputation for missing values. ” Our news reporters obtained a quote from the research from Lund University: “Thi s task is crucial for ensuring data integrity and deriving meaningful insights. In response to this challenge, we present Xputer, a novel imputation tool that a deptly integrates Non-negative Matrix Factorization (NMF) with the predictive st rengths of XGBoost. One of Xputer’s standout features is its versatility: it sup ports zero imputation, enables hyperparameter optimization through Optuna, and a llows users to define the number of iterations. For enhanced user experience and accessibility, we have equipped Xputer with an intuitive Graphical User Interfa ce (GUI) ensuring ease of handling, even for those less familiar with computatio nal tools. In performance benchmarks, Xputer often outperforms IterativeImputer in terms of imputation accuracy. Furthermore, Xputer autonomously handles a dive rse spectrum of data types, including categorical, continuous, and Boolean, elim inating the need for prior preprocessing.”
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