Xputer: Bridging Data Gaps with NMF, XGBoost, and a Streamlined GUI
  Experience
Saleena Younus Lars Rönnstrand Julhash U. Kazi
The rapid proliferation of data across diverse fields has accentuated the
importance of accurate imputation for missing values. This task is crucial for
ensuring data integrity and deriving meaningful insights. In response to this
challenge, we present Xputer, a novel imputation tool that adeptly integrates
Non-negative Matrix Factorization (NMF) with the predictive strengths of
XGBoost. One of Xputer's standout features is its versatility: it supports zero
imputation, enables hyperparameter optimization through Optuna, and allows
users to define the number of iterations. For enhanced user experience and
accessibility, we have equipped Xputer with an intuitive Graphical User
Interface (GUI) ensuring ease of handling, even for those less familiar with
computational tools. In performance benchmarks, Xputer not only rivals the
computational speed of established tools such as IterativeImputer but also
often outperforms them in terms of imputation accuracy. Furthermore, Xputer
autonomously handles a diverse spectrum of data types, including categorical,
continuous, and Boolean, eliminating the need for prior preprocessing. Given
its blend of performance, flexibility, and user-friendly design, Xputer emerges
as a state-of-the-art solution in the realm of data imputation.