FAIRiCUBE Deliverable D3.1 UC exploratory data analysis

This deliverable needs to be seen as one item of a classical and logical execution of a machine learning (ML) application. Given availability/ingestion of data, we first perform an exploratory data analysis to get familiar with the data, analyse statistical parameters and distribution, check for completeness, outliers and other characteristics which could be relevant for the choice of the machine learning. This in-depth data analysis is covered by this deliverable D3.1 UC exploratory data analysis

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-31
DOI
https://doi.org/10.5281/zenodo.12664611
Primary Topic
Lepidoptera: Biology and Taxonomy
Type
article
Field-Weighted Citation Impact
0.00
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article

FAIRiCUBE Deliverable D3.1 UC exploratory data analysis

Zenodo (CERN European Organization for Nuclear Research)
Lepidoptera: Biology and Taxonomy
article

FAIRiCUBE Deliverable D3.1 UC exploratory data analysis

article en

Abstract

This deliverable needs to be seen as one item of a classical and logical execution of a machine learning (ML) application. Given availability/ingestion of data, we first perform an exploratory data analysis to get familiar with the data, analyse statistical parameters and distribution, check for completeness, outliers and other characteristics which could be relevant for the choice of the machine learning. This in-depth data analysis is covered by this deliverable D3.1 UC exploratory data analysis

Zenodo (CERN European Organization for Nuclear Research)
NILU (NO)
Openalex Percentile: Top 54%
Lepidoptera: Biology and Taxonomy
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FAIRiCUBE Deliverable D3.1 UC exploratory data analysis · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS