TPPFAM: Use of threshold and posterior probability for category reduction in fuzzy ARTMAP

Zhang, Yongquan; Ji, Hongbing; Zhang, Wenbo

doi:10.1016/j.neucom.2013.07.042

Cited by 23 publications

(2 citation statements)

References 31 publications

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“…The biased ARTMAP [12] introduced a mechanism for biasing the internal knowledge representation whenever a predictive error occurred. The TPPFAM [13] can reduce category proliferation using the threshold filtering mechanism and improving classification prediction using a dynamic Q-max rule.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Classifying Stress From Heart Rate Variability Using Salivary Biomarkers as Reference

Liew

Seera

Loo

et al. 2016

IEEE Trans. Neural Netw. Learning Syst.

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An accurate and noninvasive stress assessment from human physiology is a strenuous task. In this paper, a pattern recognition system to learn complex correlates between heart rate variability (HRV) features and salivary stress biomarkers is proposed. Using the Trier social stress test, heart rate and salivary measurements were obtained from volunteers under varying levels of stress induction. Measurements of salivary alpha-amylase and cortisol were used as objective measures of stress, and were correlated with the HRV features using fuzzy ARTMAP (FAM). In improving the predictive ability of the ARTMAPs, techniques, such as genetic algorithms for parameter optimization and voting ensembles, were employed. The ensemble of FAMs can be used for predicting stress responses of salivary alpha-amylase or cortisol using heart rate measurements as the input. Using alpha-amylase as the stress indicator, the ensemble was able to classify stress from heart rate features with 75% accuracy, and 80% accuracy when cortisol was used.

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Section: Literature Reviewmentioning

confidence: 99%

“…Similar to the sequencing problem above, determining the optimal combination of parameter settings is an optimization problem. As stated in the literature review, several variants of the basic ARTMAP architecture have been developed to address the above issues, including Gaussian ARTMAP [11], biased ARTMAP [12], and TPPFAM [13].…”

Section: A Fuzzy Artmapmentioning

confidence: 99%