Table 5.

State detection: classifiers and specifications.

Classifier	Specifications
Random Forest	n_estimators: 500, criterion = ‘gini’, max_depth:8, min_samples_split = 8, min_samples_leaf = 10
Support Vector Machine	kernel = ‘rbf’, degree = 3, gamma = ‘auto_deprecated’, C = 1.0, tol = 0.001, cache_size = 200
K–Nearest Neighbors	n_neighbors = 50, weights = ‘uniform’, algorithm = ‘auto’, leaf_size = 40, p = 2, metric = ‘minkowski’
Naïve Bayes	Gaussian