Add to ORKGKernel machines such as Support Vector Machines (SVMs) have been widely used in various data mining applications with good generalization properties. Performance of SVMs for solving nonlinear problems is highly affected by kernel functions. The complexity of SVMs training is mainly related to the size of a training dataset. How to design a powerful kernel, how to speed up SVMs training and how to train SVMs with millions of examples are still challenging problems in the SVMs research. For these important problems, powerful and flexible kernel trees called Evolutionary Granular Kernel Trees (EGKTs) are designed to incorporate prior domain knowledge. Granular Kernel Tree Structure Evolving System (GKTSES) is developed to evolve the structure...
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on t...
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on t...
Kernel methods, a new generation of learning algorithms, utilize techniques from optimization, stati...
Kernel machines such as Support Vector Machines (SVMs) have been widely used in various data mining ...
Kernel machines such as Support Vector Machines (SVMs) have been widely used in various data mining ...
In this paper we embed evolutionary computation into statistical learning theory. First, we outline ...
In this paper we embed evolutionary computation into statistical learning theory. First, we outline...
With emergence of biomedical informatics, Web intelligence, and E-business, new challenges are comin...
With emergence of biomedical informatics, Web intelligence, and E-business, new challenges are comin...
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on t...
Abstract. Kernel-based learning presents a unified approach to machine learning problems such as cla...
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on t...
In this paper we embed evolutionary computation into statistical learning theory. First, we outline...
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on t...
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on t...
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on t...
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on t...
Kernel methods, a new generation of learning algorithms, utilize techniques from optimization, stati...
Kernel machines such as Support Vector Machines (SVMs) have been widely used in various data mining ...
Kernel machines such as Support Vector Machines (SVMs) have been widely used in various data mining ...
In this paper we embed evolutionary computation into statistical learning theory. First, we outline ...
In this paper we embed evolutionary computation into statistical learning theory. First, we outline...
With emergence of biomedical informatics, Web intelligence, and E-business, new challenges are comin...
With emergence of biomedical informatics, Web intelligence, and E-business, new challenges are comin...
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on t...
Abstract. Kernel-based learning presents a unified approach to machine learning problems such as cla...
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on t...
In this paper we embed evolutionary computation into statistical learning theory. First, we outline...
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on t...
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on t...
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on t...
Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on t...
Kernel methods, a new generation of learning algorithms, utilize techniques from optimization, stati...