2016, Clustering and Cross Validation

Identification of Hazardous Areas for Priority Landmine Clearance: AI for Humanitarian Mine Action

ML @ CMU

NOVEMBER 7, 2024

In close collaboration with the UN and local NGOs, we co-develop an interpretable predictive tool for landmine contamination to identify hazardous clusters under geographic and budget constraints, experimentally reducing false alarms and clearance time by half. Validation results in Colombia. RELand is our interpretable IRM model.

Clustering

Clustering Cross Validation Machine Learning Machine Learning

Meet the winners of Phase 2 of the PREPARE Challenge

DrivenData Labs

MAY 1, 2025

Solvers used 2016 demographics, economic circumstances, migration, physical limitations, self-reported health, and lifestyle behaviors to predict a composite cognitive function score in 2021. Cluster 0 was in English and included many people talking to an Alexa. Cluster 1 and 2 were both Spanish. Cluster 3 was Mandarin.

Decision Trees

Decision Trees Clustering Algorithm Machine Learning

Data Science Current

Identification of Hazardous Areas for Priority Landmine Clearance: AI for Humanitarian Mine Action

Meet the winners of Phase 2 of the PREPARE Challenge

Webinars

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