Analysis of Honey Production with Environmenta Variables
Yükleniyor...
Dosyalar
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Regression algorithms are included in the supervised learning techniques of machine learning. Regression covers the operations of estimating the variable with the class label (output variable) by using the numerical values in a data with regression algorithms. When the desired performances cannot be achieved with the existing regression algorithms for a problem, Ensemble Learning models are applied. In the Ensemble Learning model, multiple predictive algorithms come together and aim to achieve a higher success than the success of an algorithm alone. In this study, honey production problem was estimated with Support vector machines. Multi-layer Perceptron Regressor, KNeighborsRegressor, Voting Regressor, RandomForestRegressor, AdaBoostRegressor, BaggingRegressor, GradientBoostingRegressor and the results were compared. It was observed that the ensemble learning models increased the prediction success with the regression processes. © 2021 IEEE
Açıklama
6th International Conference on Computer Science and Engineering, UBMK 2021 -- 15 September 2021 through 17 September 2021 -- 176826
Anahtar Kelimeler
Ensemble learning, Migratory beekeeping, Regression, Supervised learning, Food products, Learning algorithms, Support vector machines, Class labels, Ensemble learning, Honey production, Learning models, Migratory beekeeping, Numerical values, Output variables, Performance, Predictive algorithms, Regression algorithms, Regression analysis
Kaynak
Proceedings - 6th International Conference on Computer Science and Engineering, UBMK 2021
