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Use Correlation Coefficients in Gaussian Process to Train Stable ELM Models.

, , , and . PAKDD (1), volume 9077 of Lecture Notes in Computer Science, page 405-417. Springer, (2015)

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An advancing investigation on reduct and consistency for decision tables in Variable Precision Rough Set models., , , and . FUZZ-IEEE, page 1496-1503. IEEE, (2014)A comparative study among different kernel functions in flexible naïve Bayesian classification., , , and . ICMLC, page 638-643. IEEE, (2011)Comparison of geometric and arithmetic means for bandwidth selection in Nadaraya-Watson kernel regression estimator., , , and . ICMLC, page 999-1004. IEEE, (2013)Impact of Variances of Random Weights and Biases on Extreme Learning Machine., , , and . JSW, 11 (5): 440-454 (2016)Random weight network-based fuzzy nonlinear regression for trapezoidal fuzzy number data., , , , and . Appl. Soft Comput., (2018)Fuzziness based semi-supervised learning approach for intrusion detection system., , , , and . Inf. Sci., (2017)A Further Investigation on the Reliability of Extreme Learning Machines., , , , and . ICDM Workshops, page 1031-1037. IEEE Computer Society, (2014)A new kernel density estimator based on the minimum entropy of data set., , , and . Inf. Sci., (2019)Imbalanced ELM Based on Normal Density Estimation for Binary-Class Classification., , , and . PAKDD Workshops, volume 9794 of Lecture Notes in Computer Science, page 48-60. Springer, (2016)Self-adaptive Weighted Extreme Learning Machine for Imbalanced Classification Problems., , , and . PAKDD (Workshops), volume 10526 of Lecture Notes in Computer Science, page 116-128. Springer, (2017)