Classification of Agricultural Emissions Among OECD Countries with Unsupervised Techniques
Agricultural emissions represent greenhouse gas emissions from crop and livestock production. There are various estimates on agricultural emissions, however on average about 14 to 25 percent of total global emissions comes from agriculture. The main goal of this paper was to present distribution of...
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| Format: | Article |
| Language: | English |
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Warsaw University of Life Sciences Press
2018-12-01
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| Series: | Zeszyty Naukowe Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie. Problemy Rolnictwa Światowego |
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| Online Access: | https://prs.sggw.edu.pl/article/view/2787 |
| _version_ | 1811222529420820480 |
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| author | Adam Andrzejuk |
| author_facet | Adam Andrzejuk |
| author_sort | Adam Andrzejuk |
| collection | DOAJ |
| description | Agricultural emissions represent greenhouse gas emissions from crop and livestock production. There are various estimates on agricultural emissions, however on average about 14 to 25 percent of total global emissions comes from agriculture. The main goal of this paper was to present distribution of agricultural emissions among OECD countries with the help of clustering analysis. Clustering analysis is one of the tools used in the field of exploratory data mining. Two methods were used in the analysis: K-means and HDBSCAN algorithms. Both techniques are part of unsupervised learning tasks, which group data into multiple clusters. Finally, an appraisal of obtained classifications was performed. |
| first_indexed | 2024-04-12T08:18:32Z |
| format | Article |
| id | doaj.art-269bc81992ae49138d3c58c62614f0de |
| institution | Directory Open Access Journal |
| issn | 2081-6960 2544-0659 |
| language | English |
| last_indexed | 2024-04-12T08:18:32Z |
| publishDate | 2018-12-01 |
| publisher | Warsaw University of Life Sciences Press |
| record_format | Article |
| series | Zeszyty Naukowe Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie. Problemy Rolnictwa Światowego |
| spelling | doaj.art-269bc81992ae49138d3c58c62614f0de2022-12-22T03:40:42ZengWarsaw University of Life Sciences PressZeszyty Naukowe Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie. Problemy Rolnictwa Światowego2081-69602544-06592018-12-0118410.22630/PRS.2018.18.4.99Classification of Agricultural Emissions Among OECD Countries with Unsupervised TechniquesAdam Andrzejuk0Warsaw University of Life Sciences – SGGW, PolandAgricultural emissions represent greenhouse gas emissions from crop and livestock production. There are various estimates on agricultural emissions, however on average about 14 to 25 percent of total global emissions comes from agriculture. The main goal of this paper was to present distribution of agricultural emissions among OECD countries with the help of clustering analysis. Clustering analysis is one of the tools used in the field of exploratory data mining. Two methods were used in the analysis: K-means and HDBSCAN algorithms. Both techniques are part of unsupervised learning tasks, which group data into multiple clusters. Finally, an appraisal of obtained classifications was performed.https://prs.sggw.edu.pl/article/view/2787agricultural economicsemissionsclassificationcluster analysisk-meanshdbscan |
| spellingShingle | Adam Andrzejuk Classification of Agricultural Emissions Among OECD Countries with Unsupervised Techniques Zeszyty Naukowe Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie. Problemy Rolnictwa Światowego agricultural economics emissions classification cluster analysis k-means hdbscan |
| title | Classification of Agricultural Emissions Among OECD Countries with Unsupervised Techniques |
| title_full | Classification of Agricultural Emissions Among OECD Countries with Unsupervised Techniques |
| title_fullStr | Classification of Agricultural Emissions Among OECD Countries with Unsupervised Techniques |
| title_full_unstemmed | Classification of Agricultural Emissions Among OECD Countries with Unsupervised Techniques |
| title_short | Classification of Agricultural Emissions Among OECD Countries with Unsupervised Techniques |
| title_sort | classification of agricultural emissions among oecd countries with unsupervised techniques |
| topic | agricultural economics emissions classification cluster analysis k-means hdbscan |
| url | https://prs.sggw.edu.pl/article/view/2787 |
| work_keys_str_mv | AT adamandrzejuk classificationofagriculturalemissionsamongoecdcountrieswithunsupervisedtechniques |