What is it about?

Data quality and data complexity affect the outcome of data analysis. This article models this contribution and presents a method for quantifying this effect on data classification results.

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Why is it important?

Anticipating the result of an analysis avoids wasting time and computational resources. The model proposed in the article allows measuring quality and complexity for better control of the analysis result.


The concept of data complexity is little known outside academia. The challenge of writing the article was bring together the concepts of data quality and data complexity and show how these two problems can be measured for better analysis results.

Rene Mendes
Universidade Presbiteriana Mackenzie

Read the Original

This page is a summary of: Modeling the combined influence of complexity and quality in supervised learning, Intelligent Data Analysis, September 2022, IOS Press, DOI: 10.3233/ida-215962.
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