A Mobile Application for Easy Design and Testing of Algorithms to Monitor Physical Activity in the Workplace

Table 7

Deafult parameters for base classifiers: -NN, NN, and DT.

Classifier	Parameters
-NN	Search algorithm: linear search with Euclidean distance
	Number of neighbors: 25
NN	Number of hidden layers: (# attributes + # classes)/2
	Learning rate: 0.3
	Momentum: 0.2
	Maximum number of epochs to train through: 500
	Attributes normalized between −1 and 1
DT (REPTree)	No depth restrictions
	Minimum total weight of the instances in a leaf: 2
	Minimum variance on all the data needed for splitting: 0.01
	Pruning
	Number of folds used for pruning: 3