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https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2001JA900118
Support vector machine as an efficient tool for high-dimensional data processing: Application to substorm forecasting Valeriy V. Gavrishchaka and Supriya B. Ganguli Science Applications International Corporation, McLean, Virginia, USA Abstract. The support vector machine (SVM) has been used to model solar wind-drivenCited by: 34
http://scholar.google.com/citations?user=sDf3Jv0AAAAJ&hl=en
Support vector machine as an efficient framework for stock market volatility forecasting VV Gavrishchaka, S Banerjee Computational Management Science 3 (2), 147-160 , 2006
https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2001JA900118
Dec 01, 2001 · The support vector machine (SVM) has been used to model solar wind‐driven geomagnetic substorm activity characterized by the auroral electrojet (AE) index.The focus of the present study, which is the first application of the SVM to space physics problems, is reliable prediction of large‐amplitude substorm events from solar wind and interplanetary magnetic field data.Cited by: 34
https://www.sciencedirect.com/science/article/pii/S0273117708000033
Nov 03, 2008 · The support vector machine (SVM), as a good alternative method of neural network, has been successfully applied to different fields because of its ability to tolerate high-dimension and/or incomplete data. In the fields of space weather, the SVM has been applied to the geomagnetic substorm forecast (Gavrishchaka and Ganguli, 2001). Despite the ...Cited by: 21
https://www.datasciencelearner.com/hyperparameters-for-the-support-vector-machines/
Support Vector Machine is one of the popular machine learning algorithms. If you have earlier build the machine learning model using a support vector machine, then this tutorial is for you. You will learn how to optimize your model accuracy using the SVM() parameters.
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