Algorithms of statistical anomalies clearing for data science applications

Algorithms of statistical anomalies clearing for data science applications

The paper considers the nature of input data used by Data Science algorithms of modern-day application domains. It then proposes three algorithms designed to remove statistical anomalies from datasets as a part of the Data Science pipeline. The main advantages of given algorithms are their relative...

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Bibliographic Details
Main Authors: Oleksii Pysarchuk, Danylo Baran, Yurii Mironov, Illya Pysarchuk
Format: Article
Language:Ukrainian
Published: Igor Sikorsky Kyiv Polytechnic Institute 2023-03-01
Series:Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï
Subjects:
anomaly removal
anomaly detection
noise removal
statistical techniques
data analysis
big data
data cleaning
Online Access:http://journal.iasa.kpi.ua/article/view/260175

Internet

http://journal.iasa.kpi.ua/article/view/260175

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