An Improved Algorithm on Least Squares Support Vector Machines

Wang, Liejun; Lai, Huicheng; Zhang, Taiyi

doi:10.3923/itj.2008.370.373

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Cited by 12 publications

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“…Kernel method can solve the problem of nonlinear classification through nonlinear transform [6]. When the input space is Euclid space or disjoint set feature space is Hilbert space, kernel method means the inner product of feature vectors derived from the process which converts input data from input space to feature space.…”

Section: Kernel Methodsmentioning

confidence: 99%

Machine Learning Algorithm For Efficiency Management Of Oil Well

Bao¹,

Ding²,

Wu³

et al. 2016

Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)

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Abstract.Based on machine learning technique and oil well efficiency project practical problem, to the complicated circumstance of oil well efficiency, non-linear machine learning support vector machines ( SVM ) shows a better analysis results than the classified prediction result of linear machine learning logistics regression ( LR ). This paper analyzed and derived the theorems and classification reason of logistics regression and support vector machines. The experiments calculated and compared the accuracies of these two algorithms under the same conditions, the result conforms the conclusion.

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Section: Kernel Methodsmentioning

confidence: 99%