Researchers often face the need to collect, explore, correlate, analyze, and classify different data sources to discover unknown relationships while performing basic steps of pattern recognition and regression analysis with classification. PEAK is a Python tool designed to make easier all of these the basic steps of pattern recognition, allowing less experienced users to reduce the time required for analysing data and promoting the discovery of unknown relationships between different data. As a working example, we applied PEAK to a specific case study dealing with a well-defined dataset representing a cohort of COVID-19 10000 digital twins with different immunological characteristics. PEAK is a freely available open-source software. It runs on all platforms that support Python3. The user manual and source code are accessible following this link: https://github.com/Pex2892/PEAK.

PEAK: A Clever Python Tool for Exploratory, Regression, and Classification Data. A Case Study for COVID-19

Sgroi G.;Parasiliti Palumbo G. A.;Di Salvatore V.;Russo G.;Pappalardo F.
2021-01-01

Abstract

Researchers often face the need to collect, explore, correlate, analyze, and classify different data sources to discover unknown relationships while performing basic steps of pattern recognition and regression analysis with classification. PEAK is a Python tool designed to make easier all of these the basic steps of pattern recognition, allowing less experienced users to reduce the time required for analysing data and promoting the discovery of unknown relationships between different data. As a working example, we applied PEAK to a specific case study dealing with a well-defined dataset representing a cohort of COVID-19 10000 digital twins with different immunological characteristics. PEAK is a freely available open-source software. It runs on all platforms that support Python3. The user manual and source code are accessible following this link: https://github.com/Pex2892/PEAK.
2021
978-3-030-88162-7
978-3-030-88163-4
Data analysis
Python3
SARS-CoV-2
UISS-SARS-CoV-2
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/514678
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact