The Categorical Data Conundrum: Heuristics for Classification Problems—A Case Study on Domestic Fire Injuries

The Categorical Data Conundrum: Heuristics for Classification Problems—A Case Study on Domestic Fire Injuries

Machine learning is well developed amongst the scientific community in terms of theoretical foundations (statistics and algorithms) and frameworks (Tensorflow, PyTorch, H2O). However, machine learning is heavily focused on numerical data, or numerical data mixed with some categorical data. For numer...

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Bibliographic Details
Main Authors: Denis Reilly, Mark Taylor, Paul Fergus, Carl Chalmers, Steven Thompson
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Categorical data
machine learning
feature encoding
algorithms
classification
fire injuries
Online Access:https://ieeexplore.ieee.org/document/9810246/

Internet

https://ieeexplore.ieee.org/document/9810246/

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