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7 Types of Data Bias in Machine Learning

Written by @Hent03 | Published on 2020/10/30

TL;DR
Data bias in machine learning is a type of error in which certain elements of a dataset are more heavily weighted and/or represented than others. A biased dataset does not accurately represent a model’s use case, resulting in skewed outcomes, low accuracy levels, and analytical errors.

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Written by
@Hent03
I'm interested in the AI trends that shape how people and technology intersect and interact.

Topics and
tags
machine-learning|learn-machine-learning|data-science|data-analysis|ai|ai-applications|artificial-intelligence|hackernoon-top-story
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