Multiple-kernel-learning-based extreme learning machine for classification design. LI X,MAO W,JIANG W. Neural Computing and Applications . 2016Li X, Mao W, Jiang W (2016) Multiple-kernel-learning-based extreme learning machine for classification design. Neural Comput Appl 27(1):175–184...
A prediction method based on multiple kernel extreme learning machine is proposed in this paper to model the complex dynamics of multivariate chaotic time series. First, the multivariate chaotic time series is reconstructed in phase space,transforming the temporal correlation into spatial correlation. ...
Multiple Kernel Learning (MKL) is a machine learning approach that allows for the integration of multiple features, such as genes, proteins, and metabolites, by combining them as different kernel matrices. These matrices are then used as input for various inference tasks, such as classification and...
The MRKELM model is developed on the basis of the multiple kernel leaning method and the reduced kernel extreme learning machine method. In the presented MRKELM, the kernel function are not fixed anymore, multiple kernels are adaptively trained as a hybrid kernel and the optimal kernel ...
Multi-objective optimization based on machine learning and non-dominated sorting genetic algorithm for surface roughness and tool wear in Ti6Al4V turning The four ML models 鈥 Linear Regression (LIN), Support Vector Machine Regression (SVR), Extreme Gradient Boosting (XGB), and Artificial Neural Net...
In order to process large image data sets with high feature dimensions, the very efficient algorithm of kernel extreme learning machine is employed to in our study to build image classifiers. In order to avoid the overflow problem, the classification strategy is improved by training classifiers on...
the School of Computer, Guangdong University of Technology, Guangzhou, China. He is also pursuing the Ph.D. degree with the Faculty of Engineering and Technology, Hasselt University, Hasselt, Belgium. His current research interests include computer vision and pattern recognition and machine learning....
In order to process large image data sets with high feature dimensions, the very efficient algorithm of kernel extreme learning machine is employed to in our study to build image classifiers. In order to avoid the overflow problem, the classification strategy is improved by training classifiers on...
Multiple-Instance Learning via an RBF Kernel-Based Extreme Learning Machine As we are usually confronted with a large instance space for real-word data sets, it is significant to develop a useful and efficient multiple-instance lea... J Wang,L Cai,X Zhao - 《Journal of Intelligent Systems》...
Classification of eeg signals using a multiple kernel learning support vector machine (Jul 2014) Google Scholar [29] P. Lang, Margaret M. Bradley The international affective picture system (iaps) in the study of emotion and attention Handbook of Emotion Elicitation and Assessment, vol. 29 (2007...