SVMS

AcronymDefinition
SVMSSierra Vista Middle School
SVMSSun Valley Middle School (USA)
SVMSSony Vegas Movie Studio
SVMSScotts Valley Middle School (California)
SVMSSmithson Valley Middle School (Spring Branch, TX)
SVMSShared Virtual Memory System
SVMSSusquehanna Valley Mycological Association (Port Crane, New York)
References in periodicals archive ?
In addition, the distance to the hyperplane indicates the confidence of classification: the farther a point from the plane, the higher the confidence of a correct classification (see also the discussion of Platt SVM below).
To generate the error curves, SVMs with polynomial (quadratic) kernel, were employed as classifiers.
For classification purposes, we used as basis of comparison both linear and RBF SVMs, SVM using PCA reduced features, and random forests (RF).
The key advantage of the SVMs is structural risk minimisation over the empirical risk minimisation which checks overfitting during model development [29, 33].
More recently, Diederich published a book on techniques to extract symbolic rules from Support Vector Machines (SVMs) [19] and Barakat and Bradley reviewed a number of rule extraction techniques applied to SVMs [20].
8 Actual 1 2 3 Predicted 3 0 0 1 0 0 0 2 0 1 8 3 Average Table 3: Performance of the proposed approach, the empirical formula, and the two-class SVMs used to determine the squeezing.
Here, a cross-validated SVM classifier was optimized using Bayesian optimization.
While several learning techniques focus on minimizing the error rate generated by the model based on the training samples, SVMs attempt to minimize the so-called structural risk.