Influence of Preprocessing Methods of Automated Milking Systems Data on Prediction of Mastitis with Machine Learning Models

• Published in: AgriEngineering Vol. 6; no. 3; pp. 3427 - 3442
• Main Authors: Kashongwe, Olivier, Kabelitz, Tina, Ammon, Christian, Minogue, Lukas, Doherr, Markus, Silva Boloña, Pablo, Amon, Thomas, Amon, Barbara
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2024
• Subjects: Accuracy; Algorithms; Automation; class; dairy cows; Dairy farms; Dairy industry; Data structures; Datasets; decision support systems; Decision trees; Disease prevention; Machine learning; Mastitis; Methods; Milk; Milking; Missing data; missing-value imputation; Multilayer perceptrons; neural networks; oversampling; performance metrics; prediction; Predictions; Preprocessing; regression analysis; Resampling; Sensors; Support vector machines; undersampling

Missing data and class imbalance hinder the accurate prediction of rare events such as dairy mastitis. Resampling and imputation are employed to handle these problems. These methods are often used arbitrarily, despite their profound impact on prediction due to changes caused to the data structure. W...