Recognition of cooking activities through air quality sensor data for supporting food journaling

Table 2 Results with minute by minute modality, online recognition

Classifiers: Random forest (denoted as R.F., max depth = 10, iterations = 10), Bayes networks (B.N., using K2 hill climbing search algorithm), Naive Bayes (N.B.), k nearest neighbor (kNN, using \(k=1\)), Logistic regression (L.R.), Support Vector Machines (SVM, using polynomial kernel and class balancing)
Numbers in italic indicate the largest value obtained in the experiment for each considered metric