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title: xD Team Members Publish Working Paper on Predicting Census Block-Status Classifications | ||
publish_date: 2024-12-23 | ||
permalink: /news/new-geo-classification-working-paper/ | ||
img_alt_text: Dashboard showing various block-level classifications | ||
image: /assets/img/news/xd-team-members-publish-working-paper-on-predicting-census-block-status-classifications.jpg | ||
image_accessibility: Dashboard showing various block-level classifications | ||
--- | ||
<p> | ||
The xD team has published another working paper on research done with the Census Geography division. In this paper we discuss the current efforts required to manually canvas addresses, the process of creating a machine learning model that can accurately identify and predict which Census blocks will require address updates, and ideas for implementing this solution with the goal of reducing costs and burdens in future Decennial Census efforts. | ||
</p> | ||
<p> | ||
The working paper is hosted on the Census Resource Library under the title | ||
<a href="https://www.census.gov/library/working-papers/2024/geo/rawal-et-al.html"> | ||
A Semi-Supervised Active Learning Approach for Block-Status Classification</a>. | ||
</p> |