Harvard Business School

Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem

Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach ...
Insurancenewsnet.com

New Insurance Economics Findings Has Been Reported by Investigators at London School of Economics and Political Science (A Random Forest Based Approach for Predicting Spreads ...

2022 JAN 04 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News-- Investigators discuss new findings in Economics - Insurance Economics. According to news reporting originating ...
CU Boulder News & Events

Long Lead Forecasting of Spring Flows in the Colorado River Using Random Forest

There is an increasing need for skillful streamflow forecasts that extend beyond a 12-month lead time (“year-2 forecasts”), particularly in basins with highly variable interannual streamflow, large ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Devdiscourse

IoT and ensemble AI transform congestion prediction in urban bus networks

Tree-based ensemble models often outperform more complex deep learning architectures when applied to structured, tabular IoT data. While neural networks excel with image and unstructured inputs, ...