Shypd.aiThe largest open index of AI toolstransdim is an open-source machine learning tool for transportation data imputation and prediction. It helps address missing data and forecast trends in spatiotemporal traffic datasets.
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transdim is an open-source machine learning project focused on transportation data imputation and prediction. It provides models to address challenges in spatiotemporal data modeling, specifically dealing with incomplete data and forecasting future traffic states. The project implements various machine learning models, mainly in Python using Numpy and Jupyter Notebooks, for tasks such as missing data imputation (e.g., random, non-random, and blockout missing patterns) and spatiotemporal prediction, both with and without missing values. It supports a range of publicly available transportation datasets, including traffic speed, volume, and passenger flow data from various cities. The project aims to create accurate and efficient solutions for these complex data challenges, offering practical examples and documentation for implementation and evaluation.
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