<p>Data points marked with an ‘x’ are used for training, while points marked as ‘o’ were used for testing.</p
In the context of support vector machines (SVM), high dimensional input vectors often reduce the com...
Classification is one of the most important tasks for different application such as text categorizat...
wev samples. Improving learning efficiency is one of most important research tasks on SVMs. It is kn...
Appropriate training data always play an important role in constructing an efficient classifier to s...
<p>Bagging results for support vector machine classification accuracy using 6 features and resamplin...
<p>The Proximal Support Vector Machine Classifier: The planes around which points of the sets A+ an...
Support vector machines (SVMs) are a classifier that uses optimal separating hyperplanes (Vapnik, 19...
Support vector machines (SVMs) are a recently developed learning system, with many applica-tions to ...
International audienceThe power of computation and large memory of computers nowadays offer a great ...
<p>Two-dimensional scatter-plots showing training data, classified data, support vectors and decisio...
Support vector machines (SVMs) are a family of machine learning methods, originally introduced for t...
Abstract. The support-vector network is a new learning machine for two-group classification problems...
<p>(a) The algorithm tries to find a boundary that maximises the distance between groups. When the i...
Support Vector Machines (SVMs) are discrete algorithms that can be used to find the maximum margin b...
We show that the orientation and location of the separating hyperplane for 2-class supervised patter...
In the context of support vector machines (SVM), high dimensional input vectors often reduce the com...
Classification is one of the most important tasks for different application such as text categorizat...
wev samples. Improving learning efficiency is one of most important research tasks on SVMs. It is kn...
Appropriate training data always play an important role in constructing an efficient classifier to s...
<p>Bagging results for support vector machine classification accuracy using 6 features and resamplin...
<p>The Proximal Support Vector Machine Classifier: The planes around which points of the sets A+ an...
Support vector machines (SVMs) are a classifier that uses optimal separating hyperplanes (Vapnik, 19...
Support vector machines (SVMs) are a recently developed learning system, with many applica-tions to ...
International audienceThe power of computation and large memory of computers nowadays offer a great ...
<p>Two-dimensional scatter-plots showing training data, classified data, support vectors and decisio...
Support vector machines (SVMs) are a family of machine learning methods, originally introduced for t...
Abstract. The support-vector network is a new learning machine for two-group classification problems...
<p>(a) The algorithm tries to find a boundary that maximises the distance between groups. When the i...
Support Vector Machines (SVMs) are discrete algorithms that can be used to find the maximum margin b...
We show that the orientation and location of the separating hyperplane for 2-class supervised patter...
In the context of support vector machines (SVM), high dimensional input vectors often reduce the com...
Classification is one of the most important tasks for different application such as text categorizat...
wev samples. Improving learning efficiency is one of most important research tasks on SVMs. It is kn...
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