Data Synthesis Technique for Categorical Pestes Des Petits Ruminants (PPR) Data Using CTGAN Model

dc.contributor.authorNyambo, Devotha
dc.contributor.authorMduma, Neema
dc.contributor.authorSinde, Ramadhani
dc.contributor.authorLyimo, Tumaini
dc.date.accessioned2024-05-22T11:57:48Z
dc.date.available2024-05-22T11:57:48Z
dc.date.issued2023-05-11
dc.descriptionThis research article was published by pre prints org,2023en_US
dc.description.abstractData scarcity is a significant challenge in the field of Machine Learning (ML), as data collection can be expensive, time‐consuming, and difficult, particularly in developing countries. This challenge is exaggerated on the need to use dataset for livestock disease predictions for early intervention and surveillance. To address this challenge, this paper presents a data synthesis method that has been used to accurately generate new data samples from few real‐world data. With much data available to train the ML models, overfitting is eliminated. We present the use of Generative Adversarial Networks mainly the Conditional Tabular Generative Adversarial Network to synthesize categorical data for training machine learning models for prediction of the Pestes des Petits Ruminants (PPR) disease. The results showed that training score became 0.89 and the cross‐ validation score was 0.87 after synthesized data was used with Random Forest algorithm. The resulting dataset can be used to support the prediction and surveillance of the Pestes des Petits Ruminants (PPR) disease. The proposed method can also be applied to any domain with categorical data, and has the potential to improve the performance of machine learning models with increased data availability.en_US
dc.identifier.urihttps://doi.org/10.20944/preprints202305.0777.v1
dc.identifier.urihttps://dspace.nm-aist.ac.tz/handle/20.500.12479/2652
dc.language.isoenen_US
dc.publisherPre prints,orgen_US
dc.subjectdata synthesisen_US
dc.subjectlivestock health;en_US
dc.subjectppr disease;en_US
dc.subjectmachine learningen_US
dc.subjectpredictionen_US
dc.titleData Synthesis Technique for Categorical Pestes Des Petits Ruminants (PPR) Data Using CTGAN Modelen_US
dc.typeArticleen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
JA_CoCSE_2023.pdf
Size:
727.84 KB
Format:
Adobe Portable Document Format
Description:
Full text

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2 KB
Format:
Item-specific license agreed upon to submission
Description: