Geospatial Feature Selection

Published: 7 May 2024| Version 1 | DOI: 10.17632/9fwf6ms3mn.1
Contributor:
Andrew ToluTaiwo

Description

This Python codes use feature selection techniques - Pearson Correlation, Information Gain, Recursive Feature Elimination, Least absolute Shrinkage and Selection Operator, Principal Component Analysis - to investigate performance of geospatial features in machine learning models.

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Categories

Geographic Information System, Machine Learning, Geospatial Data Repository

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