Data Domain Description Using Support Vectors

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(PDF) Data domain description using support vectors.

    https://www.researchgate.net/publication/221166079_Data_domain_description_using_support_vectors
    Data domain description using support vectors. ... The proposed safe region model uses support vector data description to handle cases in high-speed trains where only normal data are available ...

[PDF] Data domain description using support vectors ...

    https://www.semanticscholar.org/paper/Data-domain-description-using-support-vectors-Tax-Duin/572529f1350df7172ce2e96cd3b9f6461c12559b
    This paper introduces a new method for data domain description , inspired by the Support Vector Machine by V.Vapnik, called the Support Vector Domain Description SVDD. This method computes a sphere shaped decision boundary with minimal volume around a set of objects. This data description can be used for novelty or outlier detection. It contains support vectors describing the sphere …

Support vector domain description - ScienceDirect

    https://www.sciencedirect.com/science/article/pii/S0167865599000872
    This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier detection.Cited by: 1711

Support vector domain description - ScienceDirect

    https://www.sciencedirect.com/science/article/abs/pii/S0167865599000872
    This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier detection. A spherically shaped decision boundary around a set of objects is constructed by a set of support vectors ...Cited by: 1711

Support vector domain description - rduin.nl

    http://rduin.nl/papers/prl_99_svdd.pdf
    This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier de-

Data domain description using support vectors - CORE

    https://core.ac.uk/display/24697616
    This data description can be used for novelty or outlier detection. It contains support vectors describing the sphere boundary and it has the possibility of obtaining higher order boundary descriptions without much extra computational cost. By using the di erent kernels this SVDD can obtain more exible and more accurate data descriptions.Author: David M. J. Tax and Robert P. W. Duin

CiteSeerX — Data domain description using support vectors

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.91.7580
    This paper introduces a new method for data domain description, inspired by the Support Vector Machine by V.Vapnik, called the Support Vector Domain Description (SVDD). This method computes a sphere shaped decision boundary with minimal volume around a set of objects. This data description can be used for novelty or outlier detection.

Support Vector Data Description Machine Language

    https://dl.acm.org/doi/10.1023/B%3AMACH.0000008084.60811.49
    Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space. The boundary of a dataset can be used to detect novel data or outliers. We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier.

Support Vector Data Description

    https://dl.acm.org/citation.cfm?id=960109
    Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space. The boundary of a dataset can be used to detect novel data or outliers. We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier.Cited by: 2579

Support Vector Data Description SpringerLink

    https://link.springer.com/article/10.1023%2FB%3AMACH.0000008084.60811.49
    Jan 01, 2004 · Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space. The boundary of a dataset can be used to detect novel data or outliers. We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier.Cited by: 2579

(PDF) Data domain description using support vectors.

    https://www.researchgate.net/publication/221166079_Data_domain_description_using_support_vectors
    Data domain description using support vectors. ... The proposed safe region model uses support vector data description to handle cases in high-speed trains where only normal data are available ...

Support vector domain description - ScienceDirect

    https://www.sciencedirect.com/science/article/pii/S0167865599000872
    In Fig. 2, again a 2D artificial dataset containing 10 objects is shown.Now a support vector domain description with a Gaussian kernel for different values of s is used. The width parameter s ranges from very small (s=1.0 in the leftmost figure) to large (s=25.0 in the rightmost figure).Note that the number of support vectors decreases and that the description becomes more sphere-like.Cited by: 1711

CiteSeerX — Data domain description using support vectors

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.91.7580
    CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Abstract. This paper introduces a new method for data domain description, inspired by the Support Vector Machine by V.Vapnik, called the Support Vector Domain Description (SVDD). This method computes a sphere shaped decision boundary with minimal volume around a set of objects.

[PDF] Data domain description using support vectors ...

    https://www.semanticscholar.org/paper/Data-domain-description-using-support-vectors-Tax-Duin/572529f1350df7172ce2e96cd3b9f6461c12559b
    This paper introduces a new method for data domain description , inspired by the Support Vector Machine by V.Vapnik, called the Support Vector Domain Description SVDD. This method computes a sphere shaped decision boundary with minimal volume around a set of objects. This data description can be used for novelty or outlier detection. It contains support vectors describing the sphere boundary ...

Support vector domain description - rduin.nl

    http://rduin.nl/papers/prl_99_svdd.pdf
    This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier de-tection. A spherically shaped decision boundary around a set of objects is constructed by a set of support vectors

CiteSeerX — Support vector domain description

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.98.5622
    CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier detection. A spherically shaped decision boundary around a set of objects is constructed by a set ...

Support vector domain description - ScienceDirect

    https://www.sciencedirect.com/science/article/abs/pii/S0167865599000872
    This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier detection. A spherically shaped decision boundary around a set of objects is constructed by a set of support vectors ...Cited by: 1711

Support Vector Data Description Machine Language

    https://dl.acm.org/doi/10.1023/B%3AMACH.0000008084.60811.49
    Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space. The boundary of a dataset can be used to detect novel data or outliers. We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier.

Support Vector Data Description SpringerLink

    https://link.springer.com/article/10.1023%2FB%3AMACH.0000008084.60811.49
    Jan 01, 2004 · Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space. The boundary of a dataset can be used to detect novel data or outliers. We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier.Cited by: 2579

Support Vector Data Description - Springer

    https://link.springer.com/content/pdf/10.1023%2FB%3AMACH.0000008084.60811.49.pdf
    We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier. It obtains a spherically shaped boundary around a dataset and analogous to the Support Vector Classifier it can be made flexible by using other kernel functions. The method is made robust against outliers in the training set and is ...Cited by: 2579

(PDF) Data domain description using support vectors.

    https://www.researchgate.net/publication/221166079_Data_domain_description_using_support_vectors
    Data domain description using support vectors. ... The proposed safe region model uses support vector data description to handle cases in high-speed trains where only normal data are available ...

[PDF] Data domain description using support vectors ...

    https://www.semanticscholar.org/paper/Data-domain-description-using-support-vectors-Tax-Duin/572529f1350df7172ce2e96cd3b9f6461c12559b
    This paper introduces a new method for data domain description , inspired by the Support Vector Machine by V.Vapnik, called the Support Vector Domain Description SVDD. This method computes a sphere shaped decision boundary with minimal volume around a set of objects. This data description can be used for novelty or outlier detection.

Support vector domain description - ScienceDirect

    https://www.sciencedirect.com/science/article/pii/S0167865599000872
    This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier detection.Cited by: 1711

Support vector domain description - ScienceDirect

    https://www.sciencedirect.com/science/article/abs/pii/S0167865599000872
    This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier detection. A spherically shaped decision boundary around a set of objects is constructed by a set of support vectors describing the sphere boundary. It has the possibility of transforming the data …Cited by: 1711

Support vector domain description Semantic Scholar

    https://www.semanticscholar.org/paper/Support-vector-domain-description-Tax-Duin/d9f0e1c7e240597992232840f7cb96ceeefa1940
    This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier detection. A spherically shaped decision boundary around a set of objects is constructed by a set of support vectors describing the sphere boundary. It has the possibility of transforming the data …

Data domain description using support vectors - CORE

    https://core.ac.uk/display/24697616
    This paper introduces a new method for data domain description, inspired by the Support Vector Machine by V.Vapnik, called the Support Vector Domain Description (SVDD). This method computes a sphere shaped decision boundary with minimal volume around a set of objects. This data description can be used for novelty or outlier detection.Author: David M. J. Tax and Robert P. W. Duin

Support vector domain description - rduin.nl

    http://rduin.nl/papers/prl_99_svdd.pdf
    This paper shows the use of a data domain description method, inspired by the support vector machine by Vapnik, called the support vector domain description (SVDD). This data description can be used for novelty or outlier de-tection. A spherically shaped decision boundary around a set of objects is constructed by a set of support vectors

CiteSeerX — Data domain description using support vectors

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.91.7580
    This paper introduces a new method for data domain description, inspired by the Support Vector Machine by V.Vapnik, called the Support Vector Domain Description (SVDD). This method computes a sphere shaped decision boundary with minimal volume around a set of objects. This data description can be used for novelty or outlier detection.

Support Vector Data Description

    https://dl.acm.org/citation.cfm?id=960109
    Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space. The boundary of a dataset can be used to detect novel data or outliers. We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier.Cited by: 2579

Support Vector Data Description SpringerLink

    https://link.springer.com/article/10.1023%2FB%3AMACH.0000008084.60811.49
    Data domain description concerns the characterization of a data set. A good description covers all target data but includes no superfluous space. The boundary of a dataset can be used to detect novel data or outliers. We will present the Support Vector Data Description (SVDD) which is inspired by the Support Vector Classifier.Cited by: 2579



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