Title :
A hybrid FMM-CART model for human activity recognition
Author :
Seera, Manjeevan ; Chu Kiong Loo ; Chee Peng Lim
Author_Institution :
Fac. of Comput. Sci. & Inf. Technol., Univ. of Malaya, Kuala Lumpur, Malaysia
Abstract :
In this paper, the application of a hybrid model combining the fuzzy min-max (FMM) neural network and the classification and regression tree (CART) to human activity recognition is presented. The hybrid FMM-CART model capitalizes the merits of both FMM and CART in data classification and rule extraction. To evaluate the effectiveness of FMM-CART, two data sets related to human activity recognition problems are conducted. The results obtained are higher than those reported in the literature. More importantly, practical rules in the form of a decision tree are extracted to provide explanation and justification for the predictions from FMM-CART. This outcome positively indicates the potential of FMM-CART in undertaking human activity recognition tasks.
Keywords :
decision trees; fuzzy set theory; minimax techniques; neural nets; pattern classification; regression analysis; CART; classification and regression tree; decision tree; fuzzy min-max neural network; human activity recognition; hybrid FMM-CART model; Accelerometers; Accuracy; Complexity theory; Computational modeling; Decision trees; Legged locomotion; Training; classification and regression tree; fuzzy min-max neural network; human activity recognition; rule extraction;
Conference_Titel :
Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on
Conference_Location :
San Diego, CA
DOI :
10.1109/SMC.2014.6973904
