نتایج جستجو برای: least square support vector machine lssvm

تعداد نتایج: 1470782  

Journal: :Communications for Statistical Applications and Methods 2003

Journal: :Neurocomputing 2014
Jan Chorowski Jian Wang Jacek M. Zurada

This paper presents how commonly used machine learning classifiers can be analyzed using a common framework of convex optimization. Four classifier models, the Support Vector Machine (SVM), the Least-Squares SVM (LSSVM), the Extreme Learning Machine (ELM), and the Margin Loss ELM (MLELM) are discussed to demonstrate how specific parametrizations of a general problem statement affect the classif...

2000
Johan A. K. Suykens Lukas Lukas Joos Vandewalle

In least squares support vector machine (LS-SVM) classi-ers the original SVM formulation of Vapnik is modiied by considering equalit y constraints within a form of ridge regression instead of inequality constraints. As a result the solution follows from solving a set of linear equations instead of a quadratic programming problem. Ho wever, a d r a wback is that sparseness is lost in the LS-SVM ...

Journal: :The International Journal of Advanced Manufacturing Technology 2023

In order to realize real-time and precise monitoring of the tool wear in milling process, this paper presents a predictive model based on stacked multilayer denoising autoencoders (SMDAE) technique, particle swarm optimization with an adaptive learning strategy (PSO-ALS), least squares support vector machine (LSSVM). Cutting force vibration information are adopted as signals. Three steps make u...

2000
J A K Suykens L Lukas J Vandewalle

In least squares support vector machine (LS-SVM) classi-ers the original SVM formulation of Vapnik is modiied by considering equality constraints within a form of ridge regression instead of inequality constraints. As a result the solution follows from solving a set of linear equations instead of a quadratic programming problem. However, a drawback is that sparseness is lost in the LS-SVM case ...

Journal: :Communications for Statistical Applications and Methods 2008

Journal: :IJWMIP 2013
Sheng Zheng Changcai Yang Emile A. Hendriks Xiaojun Wang

We propose a snowing model to iteratively smoothe the various image noises while preserving the important image structures such as edges and lines. Considering the gray image as a digital terrain model, we develop an adaptive weighted least squares support vector machine (LS-SVM) to iteratively estimate the optimal gray surface underlying the noisy image. The LS-SVM works on Gaussian noise whil...

2011
Ching-Lu Hsieh Chao-Yung Hung Ching-Yun Kuo

Raw cow milk has short supply market in summer and over supply in winter, which causes consumers and dairy industry concern about the quality of raw milk whether is adulated with reconstituted milk (powdered milk). This study prepared 307 raw cow milk samples with various adulteration ratios 0%, 2%, 5%, 10%, 20%, 30%, 50%, 75%, and 100% of powdered milk. Least square support vector machine (LS-...

Journal: :International Journal of Current Microbiology and Applied Sciences 2019

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