نتایج جستجو برای: ls svm

تعداد نتایج: 32490  

Journal: :DEStech Transactions on Computer Science and Engineering 2018

2016
Peiyu Ren Yancang Li Huiping Song Lei Zhang Rongbiao Zhang

For fast detection of inorganic phosphorus fractions and their phosphorus contents in soil, a method employing near-infrared spectroscopy (NIRS) combined with partial least squares (PLS) and least squares support vector machine (LS-SVM) was proposed. Fifty soil samples for each of iron phosphate, magnesium phosphate, calcium phosphate and aluminum phosphate, with application rates of phosphate ...

Journal: :Journal of Physics: Conference Series 2013

2013
Yongni Shao Yong He

Two sensitive wavelength (SW) selection methods combined with visible/near infrared (Vis/NIR) spectroscopy were investigated to determine the levels of some trace elements (Fe, Zn) in rice leaf. A total of 90 samples were prepared for the calibration (n = 70) and validation (n = 20) sets. Calibration models using SWs selected by LVA and ICA were developed and nonlinear regression of a least squ...

Journal: :Artificial intelligence in medicine 2003
Chuan Lu Tony Van Gestel Johan A. K. Suykens Sabine Van Huffel Ignace Vergote Dirk Timmerman

In this work, we develop and evaluate several least squares support vector machine (LS-SVM) classifiers within the Bayesian evidence framework, in order to preoperatively predict malignancy of ovarian tumors. The analysis includes exploratory data analysis, optimal input variable selection, parameter estimation, and performance evaluation via receiver operating characteristic (ROC) curve analys...

2011
Jorge López Lázaro Kris De Brabanter José R. Dorronsoro Johan A. K. Suykens

Least-Squares Support Vector Machines (LS-SVMs) have been successfully applied in many classification and regression tasks. Their main drawback is the lack of sparseness of the final models. Thus, a procedure to sparsify LS-SVMs is a frequent desideratum. In this paper, we adapt to the LS-SVM case a recent work for sparsifying classical SVM classifiers, which is based on an iterative approximat...

Journal: :Medical engineering & physics 2009
Hong-Bo Xie Yong-Ping Zheng Jing-Yi Guo Xin Chen Jun Shi

Sonomyography (SMG) is the signal we previously termed to describe muscle contraction using real-time muscle thickness changes extracted from ultrasound images. In this paper, we used least squares support vector machine (LS-SVM) and artificial neural networks (ANN) to predict dynamic wrist angles from SMG signals. Synchronized wrist angle and SMG signals from the extensor carpi radialis muscle...

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 ...

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: :Int. J. Intelligent Computing and Cybernetics 2008
József Valyon Gábor Horváth

Support vector machines (SVMs), have proven to be effective for solving learning problems, and have been successfully applied to a large number of tasks. Lately a new technique, the Least Squares SVM (LS-SVM) has been introduced. This least squares version simplifies the required computation, but sparseness –a really attractive feature of the standard SVM– is lost. To reach a sparse model, furt...

نمودار تعداد نتایج جستجو در هر سال

با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید