Linear SVMs
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Supervised, Semi-supervised, and Unsupervised Learning. Kernel Based Algorithms for Mining Huge Data Sets. Companion web sites of the book. Te-Ming Huang, Vojislav Kecman, Ivica Kopriva. Series Studies in Computational Intelligence, Vol 17. Springer Verlag, Berlin, Heidelberg, 2006. This is the first book that treats the fields of. Supervised, semi-supervised and unsupervised machine learning.
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Linear SVM is the newest extremely fast. Machine learning data mining algorithm for solving multiclass. Classification problems from ultra large. Data sets that implements an original proprietary version of a cutting plane algorithm. For designing a linear support vector machine. LinearSVM is a linearly scalable routine. Meaning that it creates an SVM model in a CPU time which scales linearly. Efficiency in dealing with extra large data sets say, several millions training data pairs,. Data set Table.PARSED CONTENT
The web site linearsvm.com had the following in the web site, "Linear SVM is the newest extremely fast." We noticed that the webpage stated " Machine learning data mining algorithm for solving multiclass." It also said " Classification problems from ultra large. Data sets that implements an original proprietary version of a cutting plane algorithm. For designing a linear support vector machine. LinearSVM is a linearly scalable routine. Meaning that it creates an SVM model in a CPU time which scales linearly. Efficiency in dealing with extra large data sets say, several millions training data pairs,."SEEK SIMILAR DOMAINS
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