Applying the Geostatistical Eigenvector Spatial Filter Approach into Regularized Regression for Improving Prediction Accuracy for Mass Appraisal

Applying the Geostatistical Eigenvector Spatial Filter Approach into Regularized Regression for Improving Prediction Accuracy for Mass Appraisal

Prediction accuracy for mass appraisal purposes has evolved substantially over the last few decades, facilitated by the evolution in big data, data availability and open source software. Accompanying these advances, newer forms of geo-spatial approaches and machine learning (ML) algorithms have been...

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Bibliographic Details
Main Authors: Michael McCord, Daniel Lo, Peadar Davis, John McCord, Luc Hermans, Paul Bidanset
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Applied Sciences
Subjects:
eigenvector spatial filtering
penalized machine learning
mass appraisal
prediction accuracy
elastic-net regularized regression
Online Access:https://www.mdpi.com/2076-3417/12/20/10660

Internet

https://www.mdpi.com/2076-3417/12/20/10660

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