Weighted Classification of Machine Learning to Recognize Human Activities

Table 1

The different characteristics of ML and deep learning as regards the HAR system.

Process	ML	Deep learning
Preprocessing	Preprocessing is required and necessary for the performance	Preprocessing is not required; also normalization method
Features collection	(i) Depends on manual extraction	(i) Learns to extract the features directly
	(ii) Avoids complicated activities	(ii) Temporal and spatial dependence with scaling features automatically
	(iii) Considers feature selection with reduction technique
	(iv) Fails to handle variability and similarity class
Learning process	(i) Considers small training data	(i) Works with large data
	(ii) Less memory and computational time are needed	(ii) Works well with high complexity and computation
		(iii) Needs special hardware to perform training